NeuralSight
Neural Labs Africa aims to tackle the challenges faced by healthcare providers in accurately diagnosing and treating various medical conditions using medical imaging technologies such as X-ray, MRI, CT scans, and ultrasound. Medical imaging technologies have significantly improved medical diagnosis and treatment. However, the interpretation of these images by healthcare professionals can be subjective, prone to errors, and may require a considerable amount of time, leading to delayed diagnoses and treatments, and increased healthcare costs. We seek to address these challenges by integrating our machine learning algorithms that can analyze medical images accurately and quickly, leading to faster and more accurate diagnoses and treatments.
Additionally, Neural Labs Africa aims to address the issue of healthcare disparities in medical imaging by creating more accessible and affordable diagnostic tools. In many developing countries and rural areas, access to medical imaging technology is limited or non-existent, leading to delayed diagnoses and treatments, and increased morbidity and mortality rates. Our solutions will bridge this gap by offering low-cost, medical imaging technologies that can be used in remote areas, and machine learning algorithms that analyze these images with high accuracy. By doing so, Neural Labs Africa will improve healthcare outcomes, reduce healthcare costs, and ultimately save lives.
Our proprietary AI platform uses computer vision deep learning and machine learning to offer a great opportunity to enhance and augment radiology services, thereby relieving the bottleneck in medical imaging diagnosis. NeuralSight™ is capable of labeling different diseases at a rate of 1000 x-rays per minute, which is 1000 times faster than a human being! Through our innovative and transformational platform, we believe that NeuralSight™ will add significant value to our clinical colleagues as well as improve patient care relieving the burden of diseases in Africa.
Our company’s, solution aims to serve healthcare providers, including doctors, radiologists, and medical professionals, as well as patients. Our goal is to directly and meaningfully improve their lives by enhancing the accuracy, efficiency, and accessibility of medical imaging diagnosis and treatment.
Our target population includes healthcare providers, hospitals, diagnosticclinics, imaging centers, medical equipment manufacturers and research institutions who rely on medical imaging for diagnosing and monitoring various conditions, as well as patients who undergo imaging procedures. By developing advanced AI algorithms and integrating them into existing medical imaging systems, we strive to address their needs in the following ways:
Our AI algorithms are designed to assist healthcare providers in analyzing medical images with higher accuracy and precision. By leveraging machine learning and deep learning techniques, we can provide enhanced detection, segmentation, and classification of abnormalities, enabling more accurate diagnoses and treatment planning.
Our solutions are developed to improve workflow efficiency for healthcare providers. By automating routine tasks such as image analysis, measurement, and annotation, our technology helps save valuable time, allowing medical professionals to focus more on patient care, interpretation, and decision-making.
We aim to make medical imaging more accessible and affordable for patients. By leveraging AI to improve the efficiency of image interpretation, we can potentially reduce wait times for diagnosis and treatment, leading to better patient outcomes. Additionally, our technology has the potential to decrease costs associated with medical imaging, making it more affordable for patients.
To understand the needs of healthcare providers and patients, we continuously engage in extensive research and collaboration with medical professionals, hospitals, and healthcare institutions. We actively seek their feedback, insights, and domain expertise to develop solutions that align with their requirements. By conducting user surveys, interviews, and pilot studies, we gather valuable information about the challenges they face and the areas where our AI technology can have the most impact.
Through ongoing dialogue and collaboration, we iterate and refine our solutions to ensure they effectively address the specific needs of our target population. By continuously seeking input from end-users, we strive to create user-centric solutions that can directly improve the lives of healthcare providers and patients, ultimately enhancing the quality of healthcare delivery in the field of medical imaging.
We have a team with a combined 70 years of experience and a mix of backgrounds in healthcare, machine learning project management, and business development. Our team has a strong understanding of the healthcare industry and the specific problem we are trying to solve, as well as the appropriate technical expertise to develop and implement our AI solution. Additionally, having a diverse and strong project management and communication skilled team ensures that the solution is delivered on time and effectively integrated into the healthcare system.
- Improve the rare disease patient diagnostic journey – reducing the time, cost, resources, and duplicative travel and testing for patients and caregivers.
- Kenya
- Growth: An organization with an established product, service, or business model that is rolled out in one or more communities
Funding where funds will be focused towards helping us establish
markets within different demographic regions East and West Africa.
Meeting like-minded people and industry peers are a major motive for attending the program. This will broaden our knowledge and solve challenges.
We will also be able to learn a lot about things that are new to our field such as new methodologies, unreleased data, or learning from thought-leaders.
It also will give us an opportunity to share our thoughts and efforts with others.
Attending the program has several benefits not only will we learn about different areas of research in our field, but there are also many sessions for professional development and career counseling in which we consider very essential to our startup.
Supporting existing community initiatives that align with our goals. This could involve volunteering time and resources, and offering expertise. By actively supporting local initiatives, to demonstrate the commitment to the community's well-being and build strong relationships with community members.
Actively involve community members in the decision-making process related to our project. Seek their input, opinions, and suggestions to ensure that their voices are heard and their needs are addressed. By involving the community, we not only build trust but also ensure that our company aligns with their aspirations.
We have a unique technology or algorithm that sets the company apart from others in the market
which is a major differentiating factor. We have developed a unique machine learning technique that outperforms others in the field, giving us a competitive edge.
We also have access to strong, large, high-quality data sets which are crucial for training and evaluating our AI models. We therefore have an advantage over competitors who do not have access to the same data.
Neural Labs has deep domain expertise in a specific area of healthcare that is radiology.
We have built strong partnerships with key stakeholders in the healthcare industry.
Our company possess the ability to scale its products and services to meet the needs of a large customer base which is attractive to potential investors and customers.
We have put a strong emphasis on user-centered design and user experience can create products and services that are more intuitive and easier to use, which can be a competitive advantage.
We have a transparent and honest approach about our data sources, methods, and limitations, and are willing to work with customers to address any concerns to build trust and win customers.
Continue conducting clinical studies and trials to validate the accuracy and effectiveness of the our AI algorithms in real-world medical settings. We also want to conduct beta testing of the platform with a small group of patients and healthcare professionals to identify any issues or areas for improvement. Expand the platform's reach and impact by partnering with hospitals, clinics, and other healthcare providers, as well as by developing new features and services based on customer feedback and market demand.
Obtain regulatory approval from relevant authorities such as the FDA to ensure compliance with medical regulations and standards.
Launch the platform to the public, offering personalized medical diagnosis and treatment recommendations to patients around the world.
Expand the platform's reach and impact by partnering with hospitals, clinics, and other healthcare providers, as well as by developing new features and services based on customer feedback and market demand.
Expand the platform's reach and impact to new markets and regions, collaborating with local healthcare providers and adapting to local regulatory requirements.
Accuracy Metrics:
Level: Operational
Description: Accuracy metrics measure the performance of the AI algorithms in correctly identifying and diagnosing medical conditions from the imaging data. This KPI assesses the sensitivity, specificity, positive predictive value, negative predictive value, and overall accuracy of the AI system. It helps determine the efficacy of the AI models and their ability to provide accurate diagnoses.
Turnaround Time:
Level: Operational
Description: Turnaround time measures the speed at which the AI medical imaging system processes and analyzes the imaging data to deliver results or diagnoses. It includes the time from data ingestion to the availability of results for medical professionals. Reducing turnaround time is crucial for improving efficiency and enabling timely patient care.
Cost per Diagnosis:
Level: Financial Description: Cost per diagnosis measures the financial efficiency of the AI medical imaging company by evaluating the cost associated with generating a diagnosis or report. It includes factors such as infrastructure costs, algorithm development and maintenance expenses, computational resources, and human expertise involved in reviewing and validating results. This KPI helps assess the profitability and cost-effectiveness of the company's operations
In a continent with over one billion people, under resourced healthcare systems and inadequate specialist the World Health Organization estimates that diseases cost the Africa region 2.4 trillion international dollars. This creates need for the use of revolutionary technologies to solve the existing constrain. Neural Labs Africa technology comes in handy to solve this problem in a threefold approach. One ensuring real-time diagnosis. Secondly, cases of misdiagnosis are a large contributor to diseases burdens in Africa. Specialists in Africa works for up to three hospitals thus creating high occurrences of overwhelmed workload. This means they can rely on our technology to screen images in real time and work towards confirming suggested pathologies by the technology. Thirdly, the expensive consultation and lab fees since there are limited resources that will need to cater for specialists’ costs. Using our technology will make specialist workload eases and reduce such costs thus providing a friendly pricing model to patients. We therefore believe that the use of AI to solve the overwhelming UN Strategic Development Goal 3 Good Health and Wellbeing has the potential to ensure that Africa improves its healthcare system.
Our proprietary AI platform uses computer vision deep learning and machine learning to offer a great opportunity to enhance and augment radiology services, thereby relieving the bottleneck in medical imaging diagnosis. NeuralSight™ is capable of labeling different diseases on x-rays at a rate of 1000 x-rays per minute, which is 1000 times faster than a human being! Through our innovative and transformational platform, we believe that NeuralSight™ will add significant value to our clinical colleagues as well as improve patient care relieving the burden of diseases in Africa.
It's important to note that, as the field of AI health tech is relatively new and rapidly evolving, what makes a company unique today may not be the same a few years from now, so it's important to stay up-to-date on the latest developments and trends in the industry.
- A new technology
- Artificial Intelligence / Machine Learning
- Imaging and Sensor Technology
- For-profit, including B-Corp or similar models
8 fulltime 3 part time
Neural Labs Africa was founded in January 7th 2021. We have been in operation for 2 years were we have a team of 8 individuals who are working full time on the solution.
We have a user-centered design that understands the needs and preferences of a diverse range of users. As we have involved people from different backgrounds, gender, cultures, and abilities in the design process, thus our product is more accessible, relevant, and effective.
Our products are also affordable and accessible to people with different income levels and this promotes inclusion.
We have also collaborated with diverse stakeholders, such as community groups (local doctors), non-profits (UNICEF), and government agencies (Ministry of TB in Senegal), for inclusion. Thus, we have ensured that we co-creating our solutions with community members and involving experts from different fields in the design process.
Our business model revolves around providing advanced AI-powered products and services to healthcare providers, including hospitals, clinics, and medical imaging centers. Our primary customers are medical professionals, such as doctors, radiologists, and specialists, who rely on accurate and timely diagnoses to provide effective patient care. Our services cater to radiologists, hospitals, research institutions and diagnostic laboratories, who pay on both a transactional and subscription basis.
- Product and Services
We offer a comprehensive suite of AI-based medical imaging software that integrates seamlessly with existing medical imaging systems. Our software employs advanced algorithms to assist in image analysis, detection, segmentation, and classification of abnormalities, providing valuable insights to healthcare providers.
We provide AI-driven decision support tools that aid medical professionals in interpreting complex medical images and making more informed diagnoses. These tools leverage deep learning and pattern recognition algorithms to highlight potential areas of concern and provide recommendations, enabling improved clinical decision-making.
Our AI technology automates routine tasks, streamlines workflows, and enhances productivity in medical imaging departments. By automating image analysis, measurement, and reporting, we help healthcare providers save time, reduce errors, and improve overall efficiency.
We offer consultation services to healthcare providers to assist with the integration and implementation of our AI solutions. Additionally, we provide ongoing technical support and updates to ensure optimal performance and address any customer inquiries or concerns.
- Revenue Generation:
We offer our imaging software and decision support tools through licensing and subscription models. Healthcare providers can choose from various licensing options based on their specific needs, such as per-user licenses or department-wide subscriptions.
We provide service contracts to ensure ongoing technical support, software updates, and maintenance for our customers. These contracts help healthcare providers maintain the performance and reliability of our AI solutions.
We offer consultation and training services to healthcare institutions, providing expertise in integrating our technology into existing medical imaging workflows. These services are charged on a project basis or as part of a long-term partnership.
Our customers and beneficiaries, healthcare providers, value our products and services because:
Our AI technology enhances the accuracy and precision of medical imaging diagnoses, reducing the chances of misdiagnosis or missed abnormalities.
Our solutions automate repetitive tasks, saving time for medical professionals and enabling them to focus on critical decision-making and patient care.
By streamlining workflows and optimizing processes, our technology improves the overall efficiency and productivity of medical imaging departments.
Our AI-driven decision support tools provide healthcare providers with access to cutting-edge technology that helps them make more informed diagnoses and treatment decisions.
Our solutions potentially reduce costs associated with medical imaging by increasing efficiency and optimizing resource utilization.
By combining the delivery of impactful solutions with a sustainable revenue model, we aim to create a successful business that addresses the needs of healthcare providers while making a positive impact on patient outcomes and healthcare delivery.
- Organizations (B2B)
Generating revenue through the sale of our product. By Q4 2023 Neural Labs will be generating revenue by selling our services and licensing the technology to other companies. Our developed AI-powered diagnostic tools are sold to hospitals, clinics, and other healthcare providers. We will further engage in offering consulting services and training to healthcare organizations that want to integrate AI into their operations.
Business collaborations or partnerships where we partner with a larger company or organization can provide access to funding and resources, as well as a ready-made market for our technology.
Service contracts with governments and other organizations is one of our potential sources of revenue. Governments and other organizations who are willing to pay for the startup's expertise in developing and implementing AI-powered solutions to address specific health challenges. In addition, government grants that are for research and development in health tech industry.
We also engage in funding from venture capitalists, angel investors, incubators and accelerators provide funding, mentorship, and resources in exchange for equity in the company.
We have received funding from UNICEF, Startupbootcamp, MIT solve and Vilgro Africa