37 related articles

FDA approves the first blood test to aid Alzheimer's diagnosis, measuring plasma biomarkers as an alternative to costly PET scans and lumbar punctures. Learn about its mechanism, clinical significance, and limitations.

Deep analysis of GPT-5.6 Sol's core capabilities, including Ultra mode sub-agent parallel orchestration, Terminal Bench results, and competition with Claude Fable 5 and Grok 4.5.

Deep dive into how Semantica uses knowledge graphs + LLMs to auto-organize enterprise data into visual networks with AI reasoning, decision logging, and full source traceability.

Neck lymphatic drainage surgery allegedly reverses Alzheimer's symptoms based on the brain's glymphatic waste clearance system. This article analyzes the surgical rationale, controversies, and evidence-based evaluation.

Lifelong is a family-centered AI health management app with multi-member profiles, wearable integration, and AI companion Alo for conversational health logging. Deep dive into its features and market potential.

Google is exploring AI-powered body fat estimation from selfies. This article analyzes the technology's working principles, accuracy limits, data privacy risks, and regulatory challenges.

Stanford professor Fei-Fei Li discusses AI and visual science on Huberman Lab, explaining how ImageNet ignited modern AI, AI's capability boundaries, healthcare applications, and why human agency is the central question in AI development.

Harbor ATS/CRM is a recruiting management system built by frontline recruiters, designed for independent recruiters and small staffing agencies. A deep dive into its positioning and market impact.

Google's medical AI system AMIE demonstrates real-time video consultation capabilities in simulated clinical settings, enabling observe-ask-reason multimodal diagnosis. A deep dive into its breakthroughs and challenges.

Deep analysis of how Vidaya combines wearable devices, lab results, and DNA data to generate AI-powered Healthspan scores with personalized longevity plans.

SoloUno is an evidence-based digital health app using Habit Reversal Training, CBT, and gamification to help users overcome BFRBs like hair pulling, skin picking, and nail biting with a shame-free approach.

The AI industry's repeated claims that new models are "too dangerous" have severely depleted public trust. This article analyzes how AI safety warnings became marketing tactics and how to rebuild credible risk communication.

Exploring hybrid architecture design combining rule engines and machine learning in medical AI, analyzing how deterministic rules, CSP, and scoring mechanisms ensure safety in exercise prescription systems.

Deep dive into how Semantica uses graph-native architecture to solve AI context management and decision accountability challenges. Ideal for developers building trustworthy enterprise AI systems.

OpenAI's claimed AI math breakthrough faces expert allegations of research misconduct. Analysis covers transparency gaps, commercial vs. academic conflicts, benchmark pitfalls, and the need for independent verification in AI.

Multiple U.S. states led by Iowa demand OpenAI isolate AI agents in sandbox environments, sparking debate over AI autonomy, safety guardrails, and liability in the emerging era of autonomous AI systems.

Scientists found a drug that reverses autism-like brain changes in adult mice within hours, challenging assumptions about irreversible developmental windows. We examine the significance, limitations, and the long road to clinical application.

An open-source blood glucose prediction model using BERT-style Transformer architecture with only 17M parameters, running on mobile devices with DILATE and Pinball loss for 2-hour glucose forecasting.

An in-depth analysis of the UK's public health strategy positioning e-cigarettes as harm reduction tools, examining the logic behind the 95% lower-harm conclusion, key controversies, and global implications.

A Reddit user shares how ChatGPT combined with Fitbit heart rate data identified severe pneumonia, exploring AI health diagnostics value, limitations, and the future of wearable-AI health monitoring.