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.

Neural Labs Africa offers a cutting-edge AI-powered medical imaging platform that integrates with existing healthcare systems. Our solution utilizes state-of-the-art computer vision, deep learning, and machine learning algorithms to analyze medical images from various modalities such as X-ray, MRI, CT scans, and ultrasound. The platform's advanced algorithms can accurately detect and characterize infectious diseases, enabling healthcare providers to make timely and informed decisions.

Our services cater to radiologists, hospitals, and diagnostic laboratories, research institution and medical equipment manufacturers. The estimated cost of our services is structured as a subscription and transactional based model, tailored to the specific needs and scale of healthcare institutions. This approach ensures accessibility to a wide range of healthcare providers, from small clinics to large hospitals and public health organizations.

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. 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 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. Growing up in Nairobi, Kenya, I witnessed firsthand the hardships that many individuals face when trying to access quality healthcare. This personal experience ignited a deep-seated passion within me to explore the intersection of technology and healthcare, leading me into the realm of HealthTech. These are the steps that we have taken and are still in progress to ensure that we understand the needs of the people who the solution intends to service

• We have conducted market research to identify the specific health needs and challenges facing the population. 
• Engaged with stakeholders and experts in the field, such as healthcare professionals, patient groups, and policymakers, to gain a deeper understanding of the needs and concerns of the population. 
• Conducted user research to gain insights into the specific needs and preferences of the population, as well as any barriers they may face in accessing healthcare. 
• Collaborated with existing organizations working on similar problems, both to learn from their experience and to identify opportunities for partnerships and co-creation.

We have also engaged with potential users and patients throughout the design and development process to ensure that the solution is tailored to their needs and is user-friendly this was mainly done through clinical trials that have been ongoing for the past one year.  There is continuous monitoring and evaluating the impact of the AI health solution on the population to ensure that it is meeting the intended needs and to identify areas for improvement. Ultimately Neural Labs has been transparent about the limitations and ethical considerations of the AI solution and making sure that the solution is safe, secure and respects the privacy of the users.

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.

The first and foremost point to note is that our company's mission aligns with SDG 3 itself. SDG 3 is all about ensuring healthy lives and promoting well-being for people of all ages. our AI medical imaging company recognizes the significance of this goal and acknowledges its responsibility to contribute to it.

Neural Labs Africa core function is centered around medical imaging. AI-driven medical imaging technology has the potential to significantly enhance the accuracy and speed of diagnosing various medical conditions. This is particularly important for critical and time-sensitive cases. By providing quicker and more precise diagnoses, our company is indirectly contributing to improving health outcomes. Patients can receive timely treatment and intervention, which is crucial in many medical situations.

One of the challenges in achieving good health and well-being for all is addressing healthcare disparities. Not everyone has equal access to quality healthcare. Neural Labs Africa plays a role in reducing these disparities. AI technology can be deployed remotely, potentially reaching underserved and remote areas where access to expert medical personnel may be limited. This can help bridge the gap in healthcare provision, ensuring that people, regardless of their location or socioeconomic status, can benefit from advanced medical imaging and accurate diagnoses.

Ultimately, our company’s mission of enhancing the accuracy and speed of medical diagnoses contributes to improving health outcomes. When diseases and conditions are detected earlier and with greater precision, treatment can be more effective. Patients have a better chance of recovery, and healthcare resources can be used more efficiently.

AI Components

Computer vision is a fundamental component of NeuralSight™. This technology enables the system to understand and interpret visual data, such as medical images, with high accuracy. In the context of medical imaging, computer vision algorithms can identify patterns, structures, and anomalies within x-rays, making it a crucial component for disease detection.

NeuralSight™ relies on deep learning techniques, which include neural networks with multiple layers. Deep learning is particularly effective in handling complex, multi-dimensional data like medical images. The deep neural networks are trained to recognize disease-specific patterns and features in medical images, which enables the accurate labeling of various diseases.

Machine learning is an essential part of the AI platform as well. Machine learning models are used to continuously improve the system's accuracy and performance. These models can adapt and learn from new data, which is essential for maintaining and enhancing the system's diagnostic capabilities over time.

Underlying Data

The backbone of NeuralSight™ is a vast collection of medical imaging data. This data includes a wide range of medical images covering various anatomical regions and medical conditions. These images serve as the foundation for training the AI models. The quality and diversity of this data are crucial in ensuring the system's accuracy and generalizability.

The solution involves the use of proprietary data sets. These are unique and specialized collections of medical images and associated metadata. These proprietary data sets may include rare or specific cases that are not readily available in public datasets. Such data sets provide a competitive advantage, as they enhance the system's ability to diagnose a broader spectrum of diseases accurately.

Acquiring and Curating Data

To ensure the accuracy and reliability of NeuralSight™, a robust plan for acquiring and curating data is essential. The process involves:

Collaborating with healthcare institutions, hospitals, and radiology centers to access a diverse and extensive range of medical images, while maintaining patient data privacy and compliance with healthcare regulations.

Annotating the data to indicate the presence or absence of specific diseases or conditions. This process is labor-intensive and requires the expertise of radiologists or trained professionals.

Increasing the diversity of the data by techniques like rotation, flipping, and adding noise to prevent overfitting of the AI models.

Implementing a feedback loop for the AI system to learn from real-world cases, ensuring it adapts to new and emerging diseases and diagnostic challenges.

We conduct rigorous clinical validation studies to showcase the accuracy and reliability of NeuralSight. This is an essential step in ensuring that our AI diagnosis aligns with human medical expert diagnoses. This validation helps mitigate the risk of misdiagnosis or incorrect treatment recommendations, which could have serious consequences for patients.

Safeguarding patient data is a top priority. By adhering to robust data privacy and security standards, including compliance with GDPR and other relevant data protection laws, we protect patient information. This safeguards against the ethical risk of data breaches and the misuse of sensitive medical data, promoting patient trust and data integrity.

We engagement with specific regulatory bodies and agencies in each country or region of operation demonstrates a commitment to regulatory compliance. By following their requirements and standards, this ensures that NeuralSight meets necessary criteria for ethical and responsible use in the medical field. This helps mitigate legal and regulatory risks.

We adhere to prioritizing transparency in the decision-making process of the AI model which is essential. Ensuring that both medical professionals and patients understand how the AI diagnosis is generated helps mitigate ethical concerns related to the "black box" nature of AI. This transparency fosters trust and accountability.

We take active measures to mitigate biases in data collection and algorithmic design thus a proactive step in addressing ethical risks. Biases can lead to disparities in diagnosis, which may adversely affect certain demographic groups. NeuralSight is committed to a fair and unbiased diagnostic approach which helps ensure equity in healthcare.

We have implementing informed consent which we consider a cornerstone of ethical AI use. Empowering patients to make informed choices about the usage of their data is a fundamental ethical practice. Seeking explicit permission before using patient data in the AI model respects individual autonomy and privacy.

By fostering a patient-centric diagnostic experience, we prioritize the well-being and preferences of patients. This approach ensures that patients are actively involved in their healthcare decisions and trust your solution for their diagnoses.

Next Year

Within the next year, our primary impact goal is to enable real-time diagnosis and treatment for patients in marginalized communities, particularly those living on less than $5 PPP a day. We aim to reduce the need for multiple hospital visits due to delayed test results and diagnoses, saving significant costs and time for both patients and healthcare providers. We will implement our machine learning algorithms for real-time analysis of medical images, such as X-rays, MRI, CT scans, and ultrasound, at the point of care. This requires the deployment of our technology in healthcare facilities and the training of medical personnel in its use.

In the next year, our goal is to begin addressing healthcare disparities by providing more accessible and affordable diagnostic tools, particularly in rural and underserved areas. We aim to reach patients who currently have limited access to medical imaging, reducing morbidity and mortality rates. We are conducting pilots for our low-cost medical imaging solutions in targeted areas, collaborating with local healthcare facilities and organizations to ensure widespread access. This involves tailoring our solutions to the specific needs and conditions of these regions.

Next Five Years

Over the next five years, our primary impact goal is to achieve universal access to fast and accurate medical diagnoses. We want to ensure that all patients, regardless of their economic status or geographic location, have access to real-time diagnostic services, reducing healthcare costs and improving overall healthcare delivery. We will scale our technology to reach a broader population, expand partnerships with healthcare providers and governments, and focus on ensuring our solutions are cost-effective and user-friendly.

By Year 5, our goal is to significantly reduce premature mortality rates, especially among the most economically disadvantaged populations. We aim to accomplish this by providing timely and accurate medical diagnoses, allowing patients to start treatment immediately. We are continuously improving the accuracy and speed of our AI algorithms, ensuring that our solutions are optimized for detecting a wide range of medical conditions. We will also actively collaborate with healthcare providers to monitor and evaluate the impact of our technology on patient outcomes.

Our aim is to make affordable and accessible medical imaging technologies a reality in regions where they are currently scarce. We seek to reduce the gap in healthcare disparities by providing low-cost solutions that can be used in remote areas. We are currently working on cost optimization, leveraging partnerships, and innovative approaches to make our medical imaging technology accessible and affordable. This will involve continued research and development, as well as collaboration with governments and NGOs.

We have a team that comprises of: seven full time employees, four part-time employees, 2 data contractors: and 5 board members 

We have been working on our solution since 2020. However, Neural Labs Africa was officially registered in January 2021. 

We have a user-centered design that understands the needs and preferences of a diverse range of users. This is inclusive of language, incorporating diverse images and representations, or avoiding stereotypes and biases, 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. Our solution meets the needs of diverse groups of people and promote equal access and opportunity for all. By incorporating these principles into the design process, we create a more impactful and sustainable solution.

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.

Team Structure:

• Comprising the co-founders and key executives, responsible for overall strategy, partnerships, and decision-making.
• Technical Team - Comprising data scientists, machine learning engineers, and medical imaging experts, responsible for developing and maintaining the AI algorithms.
• Project Management and Operations Team- Responsible for ensuring the smooth execution of the solution, coordinating with partners, and overseeing the implementation process.
• Business Development and Sales Team- Focused on securing partnerships, client acquisition, and scaling the business.

Generating revenue through the sale of our product. By Q2 2024 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.

Our current operational cost is $5,000 per month, and we project it to increase to $8,000 per month in the next year due to anticipated changes. The increase in operational costs is due to a variety of factors, including hiring additional staff, expanding infrastructure, investing more in research and development, and scaling up our operations to meet growing demand or tackle new challenges.

We are seeking a funding of usd 100k. A significant portion of the funding will be allocated to advance our research and development efforts. We plan to enhance the capabilities of our AI algorithms, improve diagnostic accuracy, and ensure compatibility with various healthcare systems and data sources. These efforts require substantial investment in data acquisition, model development, and testing.

 To achieve widespread adoption and impact in the medical field, it is essential to conduct rigorous clinical validation and testing of our AI-based solutions. Funding will be crucial to support clinical trials, that  acquire medical data, and collaborate with healthcare institutions.

Meeting regulatory requirements in the healthcare sector is a complex and resource-intensive task. A portion of the funding will be allocated to ensure compliance with relevant regulations and certifications, this is FDA approvals.

As we grow and expand our operations, we will need to recruit top-tier talent in the fields of data science, software development, and healthcare expertise. The funding will facilitate the hiring of skilled professionals who are essential to the success of our project.

To conduct experiments and validations effectively, we require advanced infrastructure and specialized equipment. A portion of the funding will be invested in setting up and maintaining a state-of-the-art laboratory and computing infrastructure.

Effective marketing and outreach activities are crucial for promoting our solutions to healthcare providers, institutions, and patients. The funding will be used to execute marketing campaigns, attend relevant conferences, and raise awareness about our innovative solutions.

The provided seed funding would be instrumental in accelerating the development and deployment of our AI-based medical diagnostic solutions. It would enable us to invest in cutting-edge technology and expand our research and development efforts.

Access to experienced mentors within the Cure Residency program would provide invaluable guidance and expertise. This mentorship will help us refine our strategies, navigate regulatory challenges, and make informed decisions, ultimately leading to more effective solutions.

The provision of lab space would allow us to conduct hands-on experiments and tests, ensuring the robustness and accuracy of our AI models. This infrastructure is essential for rigorous testing and validation of our diagnostic tools.

The educational programs offered within the Cure Residency will enhance our team's knowledge and skills. Staying updated with the latest advancements in AI and healthcare will be critical for maintaining the quality and competitiveness of our solutions.

The networking opportunities presented by the Cure Residency would open doors to key stakeholders, potential collaborators, and investors in the healthcare industry. Building strong partnerships and connections is essential for scaling our solutions and expanding our impact.

Of all the aspects of the Cure Residency, we are most excited about the mentorship and networking opportunities. These will not only provide immediate support but also offer long-term benefits by connecting us with the right people and resources to drive our mission forward.

The Cure Residency's comprehensive support package perfectly aligns with our goals. We believe this opportunity will empower us to make a more significant and lasting impact in the field of medical diagnostics through AI-based solutions, ultimately benefiting both healthcare providers and patients. We are thrilled at the prospect of being part of this program and leveraging its resources to drive innovation and improve healthcare outcomes.