Fresh Takes & Updates:
Thoughts from the MedAsk team on generative AI in healthcare, benchmark results, symptom checker technology, product enhancements, industry trends, and beyond.
Chasing Real Impact with GenAI in Healthcare: Part 1 – Trends and Doctor Perspectives
This article explores how generative AI is being adopted by doctors, highlights emerging use cases like digital triage, and shares our insights from interviews with clinicians on how tools like MedAsk can enhance workflows without adding friction.
MedAsk Outperforms Leading LLMs and Symptom Checkers in Triage Accuracy
In this article, we benchmark MedAsk’s triage capabilities against leading large language models (LLMs) and traditional symptom checkers using real clinical cases. The results show that MedAsk sets a new standard in triage accuracy and patient safety.
How MedAsk’s Cognitive Architecture Improves ICD-10 Coding Accuracy
In this article, we introduce MedAsk’s custom cognitive architecture that achieves an 84.7% exact match accuracy rate in ICD-10 medical coding, marking a 16.2% improvement over GPT-4o. The results demonstrate how a specialized second layer built on foundation models can dramatically enhance healthcare coding reliability.
SymptomCheck Bench Update: Record Results and Disease-Specific Insights
The article presents MedAsk’s state-of-the-art results on SymptomCheck Bench, achieving 68.0% top-1 and 90.6% top-5 diagnostic accuracy, along with a detailed performance analysis across 14 disease categories.
AI Has Entered the Patient's World —Are We Ready?
This article examines the rapid adoption of AI chatbots in healthcare, their growing role in patient empowerment, and the critical steps being taken to ensure these tools remain safe and reliable as they enter mainstream use.
Introducing SymptomCheck Bench
In this article we introduce SymptomCheck Bench, a novel approach to evaluating AI agents on diagnostic accuracy in symptom checking tasks. Through this framework, we compare MedAsk’s performance against established commercial symptom checkers and demonstrate the potential of LLM-based approaches in symptom assessment.
Towards More Realistic Evaluation of Medical AI Systems
In this article we propose a new OSCE-style benchmark for evaluating medical AI systems through simulated clinical scenarios, addressing the limitations of current exam-style assessments and aiming to better reflect real-world medical practice.
The Case for Symptom Checkers
This article explores the challenges faced by traditional healthcare systems, the limitations of current symptom checkers, and how LLM-based solutions are poised to transform the way people interact with and understand their health.
Chasing Real Impact with GenAI in Healthcare:
Part 1 – Trends and Doctor Perspectives
This article explores how generative AI is being adopted by doctors, highlights emerging use cases like digital triage, and shares our insights from interviews with clinicians on how tools like MedAsk can enhance workflows without adding friction.
MedAsk Outperforms Leading LLMs and Symptom Checkers in Triage Accuracy
In this article, we benchmark MedAsk’s triage capabilities against leading large language models (LLMs) and traditional symptom checkers using real clinical cases. The results show that MedAsk sets a new standard in triage accuracy and patient safety.
How MedAsk’s Cognitive Architecture Improves ICD-10 Coding Accuracy
In this article, we introduce MedAsk’s custom cognitive architecture that achieves an 84.7% exact match accuracy rate in ICD-10 medical coding, marking a 16.2% improvement over GPT-4o. The results demonstrate how a specialized second layer built on foundation models can dramatically enhance healthcare coding reliability.
SymptomCheck Bench Update: Record Results and Disease-Specific Insights
The article presents MedAsk’s state-of-the-art results on SymptomCheck Bench, achieving 68.0% top-1 and 90.6% top-5 diagnostic accuracy, along with a detailed performance analysis across 14 disease categories.
AI Has Entered the Patient's World —Are We Ready?
This article examines the rapid adoption of AI chatbots in healthcare, their growing role in patient empowerment, and the critical steps being taken to ensure these tools remain safe and reliable as they enter mainstream use.
Introducing SymptomCheck Bench
In this article we introduce SymptomCheck Bench, a novel approach to evaluating AI agents on diagnostic accuracy in symptom checking tasks. Through this framework, we compare MedAsk’s performance against established commercial symptom checkers and demonstrate the potential of LLM-based approaches in symptom assessment.
Towards More Realistic Evaluation of Medical AI Systems
In this article we propose a new OSCE-style benchmark for evaluating medical AI systems through simulated clinical scenarios, addressing the limitations of current exam-style assessments and aiming to better reflect real-world medical practice.
The Case for Symptom Checkers
This article explores the challenges faced by traditional healthcare systems, the limitations of current symptom checkers, and how LLM-based solutions are poised to transform the way people interact with and understand their health.