Transform Healthcare with KAI’s Healthtech AI
KAI is revolutionizing healthcare in remote and underserved regions with our cutting-edge Healthtech AI. Our solutions leverage advanced AI-driven diagnostics and real-time patient monitoring to deliver faster, more accurate medical care where it’s needed most. We empower healthcare providers with tools to detect issues early, monitor patients effectively, and improve outcomes—all while maintaining the highest standards of data privacy and security. KAI’s innovations are informed by groundbreaking research in AI and healthcare, led by experts like Kavitesh Kumar Bali from A*STAR’s Centre for Frontier AI Research. For instance, Bali’s work in “Digital pathology, deep learning, and cancer: a narrative review” (2024) explores how deep learning enhances cancer diagnostics through digital pathology, directly supporting KAI’s diagnostic capabilities. His contribution to “Exploring the Business Aspects of Digital Pathology, Deep Learning in Cancers” (2024) highlights the scalability of these technologies, ensuring they can be deployed in resource-constrained settings. Additionally, Bali’s research in “Depression Detection Using BERT on Social Media Platforms” (2024) enables mental health monitoring by analyzing social media data, complementing KAI’s patient monitoring solutions. Furthermore, his earlier work, “Forecasting length of stay: Will it be clear or cloudy today?” (2022), uses AI to predict hospital length of stay, optimizing resource allocation and improving healthcare management in underserved regions. With KAI, quality healthcare isn’t a privilege; it’s a right for every community.
Explore KAI’s Foundational AI-Healthcare Research:
- Digital pathology, deep learning, and cancer: a narrative review
Published in Translational Cancer Research, 2024. This review discusses how deep learning enhances cancer diagnostics through digital pathology, a cornerstone of KAI’s diagnostic capabilities.
Link to publication - Exploring the Business Aspects of Digital Pathology, Deep Learning in Cancers
Published in Intelligence-Based Medicine, 2024. This paper examines the business implications of deploying deep learning in cancer diagnostics, ensuring KAI’s solutions are scalable and accessible in underserved regions.
Link to publication - Depression Detection Using BERT on Social Media Platforms
Published in 2024 IEEE International Conference on Artificial Intelligence in Engineering, 2024. This study uses BERT to detect depression via social media, enhancing KAI’s real-time patient monitoring for mental health.
Link to publication - Forecasting length of stay: Will it be clear or cloudy today?
Published in Intelligence-Based Medicine, 2022. This paper focuses on forecasting hospital length of stay using AI, supporting KAI’s efforts to optimize healthcare management and resource allocation in underserved communities.
Link to publication