Gelani Health AI Diagnostics

Delivers AI-powered differential diagnosis, SOAP note generation, enhanced voice-to-text, RAG enhanced multi-modal reasoning for emerging countries.

[Medscape @Medscape]

AI is becoming increasingly adept at diagnosing diseases, with some studies suggesting that advanced systems can now identify patterns that may escape the clinician’s eye and support more accurate diagnostic and treatment decisions.

However, can AI meaningfully contribute to diagnosis in clinical practice today? To continue reading tap the link: https://t.co/TSchHLezWc

[AI_4_Healthcare @AI_4_Healthcare]

First network analysis of AI diagnostic trials in sub-Saharan Africa: 11 trials, 10 countries, ZERO institutional bridges. Complete fragmentation.

@TheLancet's findings expose the structural barriers to AI diagnostics equity in Africa.

🔗https://t.co/6xw1DMB5Ho

#AIinHealthcare #GlobalHealth #Africa

[Shining Science @ShiningScience]

AI models are officially outperforming human physicians at diagnosing life-threatening conditions.

According to a Johns Hopkins study, approximately 795,000 Americans suffer permanent disability or death each year due to medical diagnostic errors, making misdiagnosis one of the most critical public health crises in the United States.

In high-pressure emergency department environments, quick and accurate decision-making is critical, yet clinicians must often make life-or-death diagnoses with extremely limited or unstructured information.

A recent study published in the journal Science evaluated how OpenAI’s advanced "o1 preview" large language model (LLM) compared to human physicians when reviewing real, messy medical charts from emergency room patients.

The findings were staggering: during the crucial, early-stage triage phase when the least information was available, the AI system correctly identified exact or near-exact diagnoses in about 67% of cases.

In contrast, experienced human physicians achieved diagnostic accuracy of only 50% to 55%. The model's ability to seamlessly handle raw, unstructured data and navigate severe uncertainty represents a potential turning point in medical technology.

Despite the AI's impressive clinical reasoning capabilities, researchers caution that this technology is not yet ready to completely replace human doctors. Emergency room workflows rely heavily on visual cues, physical touch, and empathetic patient interaction—nuanced sensory inputs that large language models cannot currently process.

Instead, experts suggest these models will serve as powerful clinical decision-support tools, acting as a "second set of eyes" to catch overlooked diagnoses or assist in developing long-term treatment plans. As AI diagnostic accuracy continues to rapidly climb, researchers are calling for rigorous, prospective clinical trials in real hospital environments to determine how humans and machines can most safely and effectively collaborate.

source: Brodeur, P. G., Buckley, T. A., Kanjee, Z., & Rodman, A. (2026). Performance of a large language model on the reasoning tasks of a physician. Science.

[nature @Nature]

A suite of AI tools is helping to speed up the process of discovering new antibiotics

https://t.co/ak4HKlcRMU

[Gelani Health AI Diagnostics @GelaniAIHealth]

Evolution of #AI #Health expands across the clincal ecosystem @GelaniAIHealth #healthtech

[Ramesh Dontha 🦉 @EntrepreneursAI]

AIHealthTech Insider: Issue #102

AI is turning routine scans and ECGs into early-warning systems for Alzheimer’s, cancer, and heart disease before symptoms appear. https://t.co/cJw8qq6AF7

[The Lancet @TheLancet]

Who's really in the loop? Rethinking oversight in AI-assisted health care

🔗 https://t.co/AZbYUKCL8X

[News from Science @NewsfromScience]

Researchers show that a type of #AI known as a large language model often outperformed physicians at diagnosing complex and potentially life-threatening conditions, including decreased blood flow to the heart, even in the fast-moving stages of real ER care when information is limited.

In early ER cases, the model identified the correct or a very close diagnosis in about 67% of cases, compared with roughly 50% to 55% for physicians. And the technology is only getting better.

Learn more: https://t.co/ke7CsHcdUq

[Gelani Health AI Diagnostics @GelaniAIHealth]

#AI scribes are transforming healthcare — recording, transcribing, and summarizing patient visits so doctors can focus on care, not paperwork. One of the many functionalities of @GelaniAIHealth #diagnostics - optimizing the #clinical workflow. #healthtech https://t.co/G0s29Ruthn

[Alex Wendland @AlexRWendland]

Excited to share Adaptive Innovation’s (@joinadaptive) $50M Series A led by @felicis and $10M Seed led by @BainCapVC.

Adaptive is an AI-native healthcare provider rebuilding the way care is delivered in America, starting with home health

[Gelani Health AI Diagnostics @GelaniAIHealth]

#healthcare orgs should move beyond generic AI automation and invest in clinically intelligent, explainable, workflow-integrated #AI. @GelaniAIHealth strives to seamlessly integrate into #clinical ecosystems providing evidenced differential #diagnostics. https://t.co/s27LSxCnii

[Gelani Health AI Diagnostics @GelaniAIHealth]

#Healthcare #AI fails because health systems aren't ready for it—not because the tech doesn't work. The algorithms are fine.
@GelaniAIHealth addresses this through its optimized #clinic workflow and holistic updated governance. #healthtech #diagnostics
https://t.co/SBz5wwRDt2

[Gelani Health AI Diagnostics @GelaniAIHealth]

All 27 EU countries are adopting AI in #healthcare, with 74% using #AI #diagnostics and 81% involving stakeholders in AI governance. @GelaniAIHealth multi-modular diagnostics focuses on the missing regions - resource constraint frontier markets #LMICS

https://t.co/HXReU7Mp1h

[Gelani Health AI Diagnostics @GelaniAIHealth]

https://t.co/sgCOjBisnh #AI #diagnostics #healthcare

[Gelani Health AI Diagnostics @GelaniAIHealth]

https://t.co/GZNWTtDSzZ #A.I. continues to make huge leaps in the #healthcare #diagnostics sector #healthtech #cdss

[Gelani Health AI Diagnostics @GelaniAIHealth]

https://t.co/HwaM2aSOMs @GelaniAIHealth aims to provide every #heath worker with tools that optmize clinical work flow, reduce #diagnostic errors and ultimately become an end to end multi-modular assistant in a resource constrained environment #healthtech

[Gelani Health AI Diagnostics @GelaniAIHealth]

https://t.co/e2FwTI0Qwk AfriMed-QA: 15K Q&A from African medical schools. Localized #AI for #healthcare isn't a nice-to-have — it's the difference between useful and harmful advice. @GelaniAIHealth takes things further - adding #clinical workflow for healthcare practioners

[Gelani Health AI Diagnostics @GelaniAIHealth]

https://t.co/LRc5cKdeIw Investment in #AI for the #healthcare ecosystem is ramping up as clear benefits in reducing #diagnostic errors, efficiency in clinical work flow, reduction in cost and various other advantages are demonstrated

[Gelani Health AI Diagnostics @GelaniAIHealth]

As #AI continues to revolutionize the #health care ecosystem, #WHO is following suit with a comprehensive guidelines for such multi-modular #diagnostic platforms as @GelaniAIHealth https://t.co/KWwyvqV5y8

[Gelani Health AI Diagnostics @GelaniAIHealth]

https://t.co/ikwuSVfrvK #healthtech #ai fascinating what AI can do the in #health space - and it is just starting