Recent Posts
Federated Learning within the leading American Hospital Network: How AffectLog Sets a New Standard in Secure Data Aggregation for the Mental Health Monitoring of the Frontline Health workers
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In today’s data-driven landscape, healthcare data is a treasure trove of insights waiting to be unlocked—especially for large hospital networks. From predictive analytics in oncology to AI-based radiology, the potential for machine learning (ML) to enhance patient care is immense. Yet concerns around data privacy, complex regulatory requirements, and the…
End-to-End Prototype using AffectLog’s Privacy-Preserving Mental Health Digital Twin Platform
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Introduction Integrating personal health data with clinical records can greatly improve the prediction and management of mental health conditions. In this prototype, we design a privacy-preserving mental health digital twin platform that unifies data from iPhone sensors, doctor’s notes, and electronic health records (EHR) to create a dynamic digital representation…
AffectLog AL360° – Technical Solution Architecture
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This document offers an in-depth exploration of the technical underpinnings of the AL360° platform — a next-generation solution developed by AffectLog to solve the pressing challenge of accessing sensitive private data in a trustworthy and regulation-aligned manner. AL360° is conceived as a full-stack, modular, and future-proof infrastructure layer for the…
AL360°: Redefining Trust and Access in the Private Data Economy
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In a data-centric world marked by surging digital footprints and ever-tightening regulatory frameworks, enterprises, researchers, and policymakers face a critical dilemma: how to responsibly access and utilise sensitive, private data without breaching trust, security, or legal boundaries. This challenge is particularly pronounced in domains like healthcare, financial services, education, and…
