MEDHINI

The idea behind the startup is very simple but very important , lack of which we are unable to make a stern healthcare system

Patients are suffering from :-

1) Patients are suffering from :Multiple tests for Diagnosing a disease,Multiple tests multiplicates to multiple costs.

2) Doctors require a clinical decision support for accurate and fast diagnosing of diseases before treatment

3) Costly diagnosing

4)Bio-Pharma requires a Predictive and real Time Drug Efficacies

5) New disease are adventing which require a Highly developed Technological Access to reduce Preventive care analogies.

6)Preventive healthcare accessibility and diagnosing could save lives of millions.

8) Remote areas,Conflict, displacement, natural disasters, Poor, Downtrodden people don't even have an access to healthcare facility, People just succumb under diseases without appropriate and accurate diagnosing.

9) Mortality rate of 92% for wrong or delayed diagnosing.

10) There is no EWS system for health .

11) Very difficult solutions for Medical Structure in lieu of complex Procedures and jargons.

12) No Predictive and Future Disease predictability analogies for any Patient to make them future ready about their health

13) No channel for Diagnosing with single Input but for multiple parameters

14) No Channel for Detailed and future disease markers

People not only suffering from lack of good healthcare system but also lack of accessibility especially people have a fear to go for disease diagnosis due to mutilple factors of cost, inaccessibility , Unavailability , Unable to diagnose right disease at right time and factors like with systemic and institutional inequities, poverty, unemployment, violence, or other factors. Most affected are underserved communities, including but not limited to, women and girls, ethnic minorities, people with disabilities, and older adults are often disproportionately affected. 

They not only suffer from diseases but from mental agony and pain and undergo high stress level which deters their health and increases the cases of mortality.

ARFICUS PRIVATE LIMITED with its product named 

MEDHINI- An Award winning Highly Innovative World's 1st Artificially Intelligent Inhouse Developed Quick, Affordable, Rapid , Accurate and  Impact Driven Diagnosing SAMD catering to 5 verticals Neurology, Nephrology, Cardiology Oncology

"MEDHINI" which is world's 1st Artificially Intelligent Preventive Healthcare ( Health Prognosis) Digital Diagnostics , Pathological and Health Future Prediction Medical SaaS Platform

provides effective clinical decision support tool with a clinically certified accuracy of 99.31% , Reducing Diagnosing TaT to just 53 seconds for chronic and complex diseases , Diagnosing Costs to just less than $7 and catering to even the remote and unassailable areas of globe.

The solution is based on the latest technology of AI with an in-house proprietary algorithm of MEdhxBERT and MedhxAKAZE.

With this solution we are trying to solve complex irregularities in Healthcare space specially for the needy people across the globe in the areas of :-

• Increase local capacity and resilience in health systems, including the health workforce, supply chains, and primary care services.- With the help of MEDHINI solution we make Screening of health, Diagnosing of Disease and People health future prediction ( We call it as Preventive Healthcare) so easy that nook and corner of the globe will get access to high- end Tech Enabled Quality Healthcare access

• Enable informed interventions, investments, and decision-making by governments, local health systems, and aid groups. - We provide the reports not only to patient but also hits to the ABDM of informed decision makers so that they could analyse the Real Time Diseases reporting in their areas and can take early informed decision if any diseases is converting any pandemic/endemic or others

• Improve accessibility and quality of health services for underserved groups in fragile contexts around the world (such as refugees and other displaced people, women and children, older adults, and LGBTQ+ individuals).- MEDHINI solution works as both Cloud Software ( With Internet Connection) and Standalone System ( Without Internet Connection) so it could be deployed in any situation and at any place

• Enable continuity of care, particularly around primary health, complex or chronic diseases, and mental health and well-being.- MEDHINI with its innovative technology serves under 5 verticals of Pulmonology, Neurology, Nephrology, cardiology and Oncology. MEDHINI provides Quick, rapid, Affordable, Accurate and Continuous High Quality Tech Enabled Healthcare for Complex and chronic diseases , Mental Health and Well being and also not only provides Screening and diagnosing but also Health Future Prediction i.e Preventive Healthcare that means we can map a patient's health for any future disease susceptibility.

  
  

  Systemic inequities and institutional failures contribute to people of color in the US having less access to care and worse health outcomes. Shocks and stresses (such as climate change, disasters, and pandemics) can worsen these disparities.  US racial equity, we will select 2-4 solutions from the US working to address these disparities for our Black & Brown Innovators in the US Program- MEDHINI solution has been specifically designed to serve across any races of the society and their upliftment.We believe all are equal and focussed section of the society require much more detailed attention. In this context MEDHINI system has been designed and tested for a Quick, Quality, Rapid, Affordable and Accurate healthcare to Black and Brown Section of the society. We believe "Black Lives Matter"

We cater to Needy sections of the society especially focussed on people suffering from destabilizing events whose lives worsened due to lack of  availability and lack of quality of health services in contexts where health systems are already weak, increasing the likelihood of death, disease, and poor mental health. The frequency and severity of crises like pandemics, forced displacement, and impacts from climate change are growing. 

We always visioned ourselves to markup that it is critical to build resilience in health systems to allow them to better prepare for, manage, and learn from shocks and stresses, while also providing critical care throughout.

Fragile contexts are not limited to large-scale or devastating situations like humanitarian crises. They can also include communities where governance is weak and unable to cope with systemic and institutional inequities, poverty, unemployment, violence, or other factors. In fragile contexts around the world, underserved communities, including but not limited to, women and girls, ethnic minorities, people with disabilities, and older adults are often disproportionately affected. 

MEDHINI is focussed upon underserved communities, including but not limited to, women and girls, ethnic minorities, people with disabilities, and older adults are often disproportionately affected.

Total Lives - MEDHINI with its solution Touched 1.76 Crore lives so far

With our with a Mission- Impact Driven and Creating sustainable Ecosystem

With our Affordable Diagnosing for all - We have saved $3 million of patients so far

With Our Future Health Prediction - 74.24 Lacs lives saved so far

Creating sustainable Ecosystem

Quick and Rapid Health Screening- MEDHINi achieved 98% reduction in diagnosis time

Quality healthcare Access to Un- assailable Geographies- 47 Remotest areas got access to High Technology Healthcare

Total Lives - MEDHINI with its solution Touched 1.76 Crore lives so far

We are visioned  with a Social Driven Approach in creating-

Early Warning System for Health

Painless and Accurate Disease Diagnosing

Mass Screening and Health Mapping

Geographical Health Analysis

MEDHINI Solution features:-

Diseases Screening Time- Just 53 seconds ( Even for Chronic diseases )

Number of Tests Just 1 Single test ( We have cut down the Number of Diagnosis tests to just 1 )

Affordable- We have slashed down the pricing to Just $ 7 (0.25x of Existing Cost)

MEDHINI's Solution Clinical Decision Support - We have Improved by  97%o f existing healthcare ecosystem

Preventive Healthcare - MEDHINI is Providing 100% Future Health mapping

Accessibilty and Mortality Reduction- MEDHINI has Improved the rate to 96%

1) Founders hailing from Doctor's background , but unable to contribute due to Experience in Technical areas and pursuing Engineering in its early days

2) Lost 4 very close people due to wrong or delayed diagnosing of criticality of disease

3) Saw very tough times where people are suffering for even a mg/l of oxygen

4) Saw people losing lives due to lack of Accurate Cure drugs and Pharma Arrangements

5)Everyone looking for New age cutting edge technologies as their saviour for high-end Medical Softwares , we believe MEDHINI could be the pivot and game-changer for Global Medical fraternity.

6) We believe that the talent and opportunities in Healthcare Could become the next big leader in the Medical Field.

7)We want to take Arficus across the globe and making Arficus the brand of brands in Health care domain.

8) Arficus is bounded with a social driven approach and visioned with an impact driven approach, so thus their founders are . With high resilience they are becoming the leaders in Healthcare Ecosystem

2.13 crore people

Support we need from Solver's community in areas:-

Cultural and market barriers- We want to deploy the solution to the last mile needy people of the society and believe solver community could helps us in that.

Financial- As we are in Scale stage so looking for financial assistance so that Solution with Discounted rates or Free of cost with the help of government regulators could be provided to needy people.

Business- Want to connect to OEM and partnerships channel for ease and quick deployment and becoming an asset lite business model

ARFICUS PRIVATE LIMITED with its product named 

MEDHINI- An Award winning Highly Innovative World's 1st Artificially Intelligent Inhouse Developed Quick, Affordable, Rapid , Accurate and  Impact Driven Diagnosing SAMD catering to 5 verticals Neurology, Nephrology, Cardiology Oncology

"MEDHINI" which is world's 1st Artificially Intelligent Preventive Healthcare ( Health Prognosis) Digital Diagnostics , Pathological and Health Future Prediction Medical SaaS Platform

provides effective clinical decision support tool with a clinically certified accuracy of 99.31% , Reducing Diagnosing TaT to just 53 seconds for chronic and complex diseases , Diagnosing Costs to just less than $7 and catering to even the remote and unassailable areas of globe.

The idea behind the startup is very simple but very important , lack of which we are unable to make a stern healthcare system

Patients are suffering from :-

1) Patients are suffering from :Multiple tests for Diagnosing a disease,Multiple tests multiplicates to multiple costs.

2) Doctors require a clinical decision support for accurate and fast diagnosing of diseases before treatment

3) Costly diagnosing

4)Bio-Pharma requires a Predictive and real Time Drug Efficacies

5) New disease are adventing which require a Highly developed Technological Access to reduce Preventive care analogies.

6)Preventive healthcare accessibility and diagnosing could save lives of millions.

8) Remote areas,Conflict, displacement, natural disasters, Poor, Downtrodden people don't even have an access to healthcare facility, People just succumb under diseases without appropriate and accurate diagnosing.

9) Mortality rate of 92% for wrong or delayed diagnosing.

10) There is no EWS system for health .

11) Very difficult solutions for Medical Structure in lieu of complex Procedures and jargons.

12) No Predictive and Future Disease predictability analogies for any Patient to make them future ready about their health

13) No channel for Diagnosing with single Input but for multiple parameters

14) No Channel for Detailed and future disease markers

People not only suffering from lack of good healthcare system but also lack of accessibility especially people have a fear to go for disease diagnosis due to mutilple factors of cost, inaccessibility , Unavailability , Unable to diagnose right disease at right time and factors like with systemic and institutional inequities, poverty, unemployment, violence, or other factors. Most affected are underserved communities, including but not limited to, women and girls, ethnic minorities, people with disabilities, and older adults are often disproportionately affected. 

They not only suffer from diseases but from mental agony and pain and undergo high stress level which deters their health and increases the cases of mortality.

MEDHINI with its solution provides a Quick, Rapid, Affordable, Accurate, Painless and Early Diseases Pre-Screening , Diseases Spread Analysis , Adjoining Enhanced Bio-Markers for added Research and Analysis and Health Future Prediction so that No-one in this globe should be left out form Quality healthcare access.

1- Creating a Sustainable, Stern and Resilient Healthcare - With the help and support of Solve and MIT we could reach out to broader mass and last mile of the society.

2- Creating a Painless and Affordable Healthcare Ecosystem- MEDHINI is on target on creating a Painless Screening and Diagnosing of Diseases , Affordable diagnosing i.e just $7 for diagnosing of even complex and chronic diseases.

3- Creating a Preventive Healthcare Ecosystem- With MEDHINI's Health Future Prediction we are envisioned to identify Diseases before suffering. A patient shouldn't suffer from Any diseases and then go for Diagnosing, But a Patient Should Know what all disease it could impact its health before suffering

4.Creating the World's 1st One stop Healthcare platform- We at MEDHINI are visioned to build highly scalable and One Stop Solution for all Diagnosis and Screening needs of a patient

5.Touching lives of Billions- MEDHINI is missioned to create a highly resilient and Stern Healthcare ecosystem to needy section of the society especially for  underserved communities, including but not limited to, women and girls, ethnic minorities, people with disabilities, and older adults.

Ensure universal access to health and health rights as agreed in accordance with the Programme of Action of the International Conference on Population and Development and the Beijing Platform for Action and the outcome documents of their review conferences

Number of countries with laws and regulations that guarantee full and equal access to women and men aged 15 years and older to sexual and reproductive health care, information and education

Enhance the use of enabling technology, in particular information and communications technology, to promote the empowerment of women

Reducing Number of new HIV infections per 1,000 uninfected population, by sex, age and key populations

Reducing Tuberculosis incidence per 100,000 population

Reducing Malaria incidence per 1,000 population

Reducing Hepatitis B incidence per 100,000 population

Increasing Healthcare Infrastructure for Number of people requiring interventions against neglected tropical diseases

Reducing Mortality rate attributed to cardiovascular disease, cancer, diabetes or chronic respiratory disease

Proportion of women of reproductive age (aged 15-49 years) who have their need for family planning satisfied with modern methods

Enhancing Coverage of essential health services

Proportion of population with large household expenditures on health as a share of total household expenditure or income

Proportion of the target population covered by all vaccines included in their national programme

Total net official development assistance to medical research and basic health sectors

Proportion of health facilities that have a core set of relevant essential medicines available and affordable on a sustainable basis

Enhancing Tech Enabled Health worker density and distribution

Enhancing Tech Enabled Healthcare Ecosystem for International Health Regulations (IHR) capacity and health emergency preparedness to prevent any New pandemic and Endemics

Reducing Percentage of bloodstream infections due to selected antimicrobial-resistant organisms

MEDHINI is The FUTURE OF HEALTHCARE. MEDHINI is creating the World's 1st SAMD Providing Rapid, Quick, Affordable , Accurate , Easy Prognosis , Diagnosis and Health Future Prediction.

MEDHINI not only save lives but also , Save from any Health Turmoil , Any Pandemic , Any Mass epidemic breakout, Ease of Healthcare infrastructure to Needy Sections of Society , underserved communities, including but not limited to, women and girls, ethnic minorities, people with disabilities, and older adults are often disproportionately affected. 

MEDHINI evidence with its research not for its benefits but also shares the new Paradigm , Knowledge with the world , Which could mutually all the Healthcare enablers could utilise and cumulatively create the best in class Healthcare Ecosystem for People across the globe.

With the leading companies of healthcare we bear much more responsibilities towards society upliftment and care access to each and every last mile sections of the society.

MEDHINI - The Future of AI Healthcare ( Tech Specifications )-

MEDHINI has existing 4 verticals of tech which provided the cross bundling :-

1. MEdhSeg- RESTNET 50 Fragmentation with KERAS STACK FIFO and Net Based Segmentation . Cross Bundling of three Enhanced features and introducing the World’s 1st 3 Cranarium Brain Structure named as MEdhSeg (Medhini Segmentation) which is significantly useful for Healthcare , Fintech and Web3 providing the Most rigid and stern Framework creating the Qualitative and Quantitative data flows with the Binary Encoders thus creating the Lake reservoirs for data Flow making large data pool with ease analysis and Result determination providing World Class In-Out Flows of tf 5 and hdf5 markers with least spacing and creating a large but light data models making the Actual Neuron structures analytical and close to Human brain 3 high grade alveoli- Neuron tf5 Segx marking thus making a true Machine learning and Artificial Intelligence model a reality.

2.MEdhRgBx- Image and Data Processing Hybrid algo of ITK, BERT, AKAZE using Hybrid CAM,Perturbation, Statistics and BPN

3.MEdhPredx- Predictive Neural And Disease Modelling using GAN,MATLAB, VDSR, federated GNNs and MEdhx CvT

4.MEdhDx- Hybrid Markup Data Lake analogies with R Markup , Block in-widening ,

5. MEdhChatx- Hybrid Chat GPT3 with Medhini GAN Trasformers cross bundling to Extensive Propulgation of Hyper NLUs creating a subset 28x28 Matrix identification knots. ( In Process )

MEdhSeg- World’s 1st 3 Cranarium Brain Structure named as

MEdhSeg (Medhini Segmentation)

We call it MEdhSeg Method that provides 3 Cranarium Brain structures for the qualitative and quantitative data structures for Offshore data load bifurcations for sustenance of Offload Data Lake structures in the Neuron structuring of 512 layers of MEDHINI AI Algorithm. The cross bundling of the three Segmentation methods and the newly developed Cross-function Also of MEdhSeg enabling the reporting items for systematic reviews and Meta-Analysis under (PRISMA) Inline where best among three SVM, KNN, Naïve Bayes, Decision Tree, Ada Boost, Random Forest, K-Mean clustering, RNN, Convolutional neural networks (CNN), Deep-CNN, Generative Adversarial Networks (GAN), and Long short-term memory (LSTM) would be chosen and the data Lake reservoirs bifurcations over the segments would be taken thus providing entropy and frequency attributes of

and

The MEdhSeg Algorithm for diversification of Data among the 500+ Neuron layers with mean Euclidean in which p, q are the two points in Euclidean n-space, and qi and pi are the Euclidean vectors starting from the origin of the space

Whereas regression is used to determine the relationship between independent and dependent variables. The equation Y represents it is equal to an X plus b, where Y is the dependent variable, an is the slope of the regression equation, x is the independent variable, and b is constant

where Y is the dependent variable, X is the independent variable; a is the intercept, b is the slope and is the residual error, Naïve Bayes which provides a way of calculating the posterior probability, P (c | x) from P(c), P(x) and P(x | c). Naïve Bayes classifier assumes that the effect of the value of an attribute (x) on a given class (c) is independent of the values of other predictors

P(c | x) is the posterior probability of class given attribute, P(x | c) is the likelihood which is the probability of the attribute given class, P(x) is the prior probability of attribute, P(c) is the prior probability of a class, k-means which is used to define k centers, one for each cluster and these centres should be placed far away from each other. This algorithm also aims at minimizing an objective function which is known as squared error function, given by :

||xi-vj|| is the Euclidean distance between xi-vj, Ci is the number of data points in ith cluster, C is the number of cluster center’s, convolution neural network which is a type

of feed-forward artificial neural network in which the connectivity pattern between its neurons is inspired by the organization of the animal visual cortex. Convolution is the first step in the process that convolution neural network undergoes

where (f*g)(t) = functions that are being convoluted, t = real number variable of functions f and g, g(?) = convolution of time function,?′= first derivative of tau function,

a recurrent neural network which is used for handling sequential data and its formula in which h(t) is a function f of the previously hidden state h(t − 1) and the current input x(t). The theta are the parameters of the function f is

Boltzmann machine, which optimizes the weights, a quantity related to the particular problem. Its main objective is to maximize the Consensus function (CF),

where Ui and Uj are the set of units, wij is the fixed weight, gradient descent which is an iterative process and is formulated by

where ? 1 is the next position,?,0 is the current position,? is the small step,∇?(?) is the direction of fastest increase) in healthcare

The New MEdhSeg Structure with Data Diversification loads and rearchitect with MAg 512x1 Architect look like

MEdhRgBx- Image and Data Processing Hybrid algo of ITK,

BERT, AKAZE using Hybrid CAM,Perturbation, Statistics and BPN

MEdhRgBx Diagnosing is a Slicing and Dicing extension designed to support the workflow of the in-bore targeted prostate imaging we call it (MEdhRgBx) . MedhRgBx was developed and tested to support transperineal diagnosing procedure in the Advanced Multimodality Image Guided Operating (AMIGO)

Capabilities Enhancements:-

• automatic processing of the patient images and Medhini system is useful for any existing system without any specification

• planning of the procedure (target localization)

• calibration of the intra-procedural image frame of reference with the

  transperineal template

• automated segmentation of the gland

• deformable intensity-based registration to support

• re-identification of the pre-procedurally defined targets in the inter and intra-

  procedural images

• automated, continuous tracking of the targets during the course of the procedure

• structured collection of the relevant data during the course of the procedure

  (images, results of segmentation and registration, target tracking)

• visualization of the inter and intra-procedural images and support of specialized

  hanging protocols to facilitate needle tracking, template and calibration device visualization, assessment of the image registration results, etc.

  MEdhRgBx includes tools for any slide image processing and tile extraction, customizable deep learning model training with dozens of supported architectures, explainability tools including heatmaps, mosaic maps, GANs, and saliency maps, analysis of activations from model layers, uncertainty quantification, and more. A variety of fast, optimized whole-slide image processing tools are included, including background filtering, blur/artifact detection, stain normalization, and efficient storage in *.tfrecords format. Model training is easy and highly configurable, with an easy drop-in API for training custom architectures.

  The Cross Bundling Enhancement of AI Also we name as MEdhRgBx provides a Proprietary Fuzzy logic which creates 4 Annotations engine :-

• Fuzzifier: The Fuzzification process is done by a Fuzzifier. It is a process of changing a crisp input value to the fuzzy set. Hence Fuzzifier is used as a mapping from observing input to fuzzy value. Cross Bundle of ( ITK X CAM Perturbation)

• Inference engine: After completing the fuzzification process, fuzzy value processed by the inference engine using a set of rules act as a collection of rules to the knowledge base. (Cross Bundle of CAM X AKAZE )

• Knowledgebase: This is the main component of the fuzzy logic system. The overall fuzzy system depends on the knowledge base. Basically, it consists of rules, structured and unstructured data also named the database. ( Cross Bundle of BERT X BPN Stats )

• Defuzzifier: The process of converting the output from the inference engine into crisp logic. Fuzzy value is an input to the defuzzification that maps fuzzy value to crisp value. ( Cross Bundle of AKAZE X ITK X CAM Perturbation )

  This Newly Developed Proprietary Algorithm of MEdhRgBx significantly improves the rapid disease prediction in Just 53 seconds with high 99.31% accuracy. The learning process begins with observations or information, such as examples, direct experience or instruction. AI methods in general and deep learning techniques in particular are vastly application-specific where a model trained for diagnosing one disease might not be able to work well for another diagnosis. The algorithms usually need to be retrained with respective medical data to be utilized for other diseases; otherwise, false diagnosis will be unavoidable.

  Thus With the Cross bundling of highly advanced tech Lagos and incision of the best in class native dorm Directories of analysis making MEdhRgBx diagnosing algorithm error free with least false positive or false negative and with higher deep delve into details of the slider analysis of the effected lesion areas with the markers of annotations created and making real Sense grassroots envision of the disease a patient is suffering to. This enables the generated release markers of MEDHINI world’s 1st with such a precision matrix analogy and Diagnosing of any errorneous spots easily.

  With the help of Cross Bundling MedhRgBx created a scaffolding, nanocomposite analysis structure offer advantages because it can simulate the extracellular matrix microenvironment in ways similar to human tissue and nerves . For example, collagen (COL) can directly or indirectly influence the process of cell proliferation, adhesion, and differentiation .To date, no one has developed MSCs and bio- nano- filament algorithmic structures and the overall data graft versus host reaction therefore, unknown about how data minuscule cells combined with algo-precison matrix could improve data pelvic floor reconstruction outcomes. With MEdhRgBx investigator the Biocompatibility of(SF/COL/PLCL) electrospun three-dimensional

algorithms structure scaffold seeded with human neuron Analysis Structure mesenchymal cell like structure of Precision matrix is being created(UC-MSCs) . MEdhRgBx created a World’s 1st inter winded Artificially Intelligent mesh applications to be used for Healthcare and Bio-Pharma Division.

MEdhPredx- Predictive Neural And Disease Modelling using

GAN,MATLAB, VDSR, federated GNNs and MEdhx CvT

The Entire Charm and secret of the MedhPredx lies in the Equation of

P(x∈R|I(x),∥∇I(x)∥)=P(I(x),∥∇I(x)

The flow is bi- directional (the surface can only expand since pR⩾0) any voxel x is eventually reached at a timeT(x) Knowing T is equivalent to knowing R or S

By default, MedhPredX reads whole data and generate analogies via Cross Bundling of Federated GANs Transformers of 4 along with In-house generated Propreiatary cuCIM structures. Although much faster than any other frameworks, it supports any formats. MEDHPredx also includes aPerforated GNN and Libvips backend, which adds support for *.scn, *.mrxs, *.ndpi, *.vms, and *.vmu files. MedhPredx algorithm should attempt to automatically associate slide names with the patient identifiers in your annotations file. After this step has completed, double check that the annotations file has a column for each annotation entry with the filename (without extension) of the corresponding data. With the cross bundling analogies of MATLAB and VDSR , Models can be trained to categorical, multi-categorical, continuous, or time-series outcomes, and the training process is highly configurable. MEdhx CvT cuCIM structures provides GPU- accelearted I/O, computer vision and image processing primitives for N- Dimensional images including:

• color conversion

• exposure

• feature extraction

• filters

• measure

• metrics

• morphology

• registration

• restoration

• segmentation

• transforms

  MEdhPredx has around 300 operations covering arithmetic, histograms, convolution, morphological operations, frequency filtering, colour, resampling, statistics and others. It supports a large range of numeric formats, from 128-bit int to 256-bit complex. Images can have any number of bands. It supports a good range of image formats, including JPEG, TIFF, PNG, WebP, FITS, Matlab, OpenEXR, PDF, SVG, HDR, PPM, CSV, GIF, Analyze, NIfTI, DeepZoom, and OpenSlide. It can also load images via ImageMagick or Graphics, Magick, letting it load formats like DICOM.

  With the Highly Advanced Cross Bundling of technical Algorithms , the Models can also be trained to a time series outcome using CPH and negative log likelihood loss. For CPH models, use ‘negative_log_likelihood’ loss and set outcomes equal to the annotation column indicating event time.

  Dice similarity coefficient improved on average by 0.99 (p < 0.0001, range 0.70–0.99)

  MEdhPredx was developed as an alternative to the expensive commercial tools and provide resilient and a highly flexible, modular and streamlined mesh generation pipeline. Intuitive interfaces and rich functionalities allow one to enjoy a wide range of mesh-based analyses, ranging from 3D volumetric image pre-processing (hole-filling, thinning and thickening), surface mesh modeling (extraction, remeshing, repairing, and smoothing) to volumetric mesh creation. Thus rasterize a close-surface to a volumetric image. For Example - The X-ray projection of the object at each angle of the CT gantry rotation produces a sinogram where the Y axis shows the angle in degrees while the X axis shows the spatial distance. With the help of Hybrid MedhPredx Feature we developed the Zeroth And Medh-Lak Filter analysing the Future Prediction of the diseases , Patient cure Time, Drug Combination therapies, Support Treatment and Ultra- Deep analogies of the patient for its own treatment and drug efficiacies prediction and Bio-Pharma Analysis for New drug Discovery Support.

MEdhDx- Hybrid Markup Data Lake analogies with R Markup ,

Block in-widening ,

MEdhDx - With the Cross bundling and enhancement precisioning of the Proprietary Algorithm made the MEdhDx realm will identify a run of n successive points on the desired side of the median line, and will recalculate / rebase the median accordingly. Each time a run occurs, the median will be rebased. This helps to track improvements over time.

The default is to plot a faceted plot, allowing to handle the axis limits. You can specify the number of columns in the faceted plot however, and you can also specify both the breaks for date labels on the x axis, and whether the y axis limits are fixed, or can vary by facet panel. It improved the :-

• Develop customized, reliable, high-performance machine learning models with minimal code

• Easily make and evaluate predictions and push them to a database

• Understand how a model makes its predictions

• Make data cleaning, manipulation, imputation, and visualization as

  simple as possible

  With the multi-modal cross bundling into the minute precision of GCSscoreBioConductor. The GCSscore package is used for the differential expression analysis of Affymetrix microarrays. It supports all ClariomS and Clariom/XTA chips, and it has full support for the following two 3' IVT GeneChips: the Mouse Genome 430 2.0 Array, and the Human Genome U133 Plus 2.0 Array. In general, MEdhPredx reads probe level information directly from array files in their native format (.CEL files), and then performs calculations on individual probe comparisons between arrays without the need for prior probe grouping summarization and normalizations steps.

  The MEdhDx algorithm is a comparative method for gene expression data analysis that performs tests of hypotheses directly from probe level data. It is based on an error model in which the detected signal is assumed to be proportional to the probe signal for highly expressed genes, but assumed to approach a background level (rather than 0) for genes with low levels of expression. This error model is used to calculate relative changes in probe intensities that converts probe signals into multiple measurements with equalized errors, which are summed over a probe set to form the significance score (S-score). The original S-score method required the mismatch (MM) probes to estimate non-specific binding (NSB) for each perfect-match (PM) probes, and the MM probes were removed the arrays beginning with the Affymetrix Whole Transcriptome (WT) style arrays. This new algorithm uses a gc-content based NSB, thus eliminating the original algorithm's dependence on MM probes. The S-score2 algorithm is capable of working on all modern Affymetrix array types (3' IVT and up). Assuming no expression differences between chips, the S-score2 output follows a standard normal distribution. Thus, a separate step estimating the probe set expression summary values is not needed and p-values can be easily calculated from the S-score2 output.

MedhDx Alongwith Ganache provides the data Meta Mask Capabilities along with efficient Quantitative data Precision and Probability distribution Scores segmentation and analytics.

MEdhChatx- Hybrid Chat GPT3 with Medhini GAN

Trasformers cross bundling to Extensive Propulgation of Hyper NLUs creating a subset 28x28 Matrix identification knots. ( In Process )-

Under Research and Development .

We cater to Needy sections of the society especially focussed on people suffering from destabilizing events whose lives worsened due to lack of  availability and lack of quality of health services in contexts where health systems are already weak, increasing the likelihood of death, disease, and poor mental health. The frequency and severity of crises like pandemics, forced displacement, and impacts from climate change are growing. 

We always visioned ourselves to markup that it is critical to build resilience in health systems to allow them to better prepare for, manage, and learn from shocks and stresses, while also providing critical care throughout.

Fragile contexts are not limited to large-scale or devastating situations like humanitarian crises. They can also include communities where governance is weak and unable to cope with systemic and institutional inequities, poverty, unemployment, violence, or other factors. In fragile contexts around the world, underserved communities, including but not limited to, women and girls, ethnic minorities, people with disabilities, and older adults are often disproportionately affected. 

MEDHINI is focussed upon underserved communities, including but not limited to, women and girls, ethnic minorities, people with disabilities, and older adults are often disproportionately affected.

Total Lives - MEDHINI with its solution Touched 1.76 Crore lives so far

With our with a Mission- Impact Driven and Creating sustainable Ecosystem

With our Affordable Diagnosing for all - We have saved $3 million of patients so far

With Our Future Health Prediction - 74.24 Lacs lives saved so far

Creating sustainable Ecosystem

Quick and Rapid Health Screening- MEDHINi achieved 98% reduction in diagnosis time

Quality healthcare Access to Un- assailable Geographies- 47 Remotest areas got access to High Technology Healthcare

Total Lives - MEDHINI with its solution Touched 1.76 Crore lives so far

We are visioned  with a Social Driven Approach in creating-

Early Warning System for Health

Painless and Accurate Disease Diagnosing

Mass Screening and Health Mapping

Geographical Health Analysis

MEDHINI Solution features:-

Diseases Screening Time- Just 53 seconds ( Even for Chronic diseases )

Number of Tests Just 1 Single test ( We have cut down the Number of Diagnosis tests to just 1 )

Affordable- We have slashed down the pricing to Just $ 7 (0.25x of Existing Cost)

MEDHINI's Solution Clinical Decision Support - We have Improved by  97%o f existing healthcare ecosystem

Preventive Healthcare - MEDHINI is Providing 100% Future Health mapping

Accessibilty and Mortality Reduction- MEDHINI has Improved the rate to 96>#/b###

MEDHINI has 2 revene models of :-

Pay per Test Basis - $7 per test

Monthly License Model- $1800 Lacs per month ( Unlimited Number of testing available )

MEDHINI operates on B2B model with its revenue stream majorly are :-

a) Hospitals, Healthcare Centers, Nursing Homes, Clinics, PHCs etc.

b) Bio-Pharma for new drug discovery support and analysis

c) Insure-Tech Sectors for Insurance Under writings, Policy issuance, Claims settlements 

d) Corporates for Employee wellness and Corporate Well Being

selling products or services, service contracts to governments, raising investment capital-  combination of all.

Revenue- $2.4 Million

Investment- $1 million

Grants - $500K