This review summarizes applications of machine learning (ML) in acute myeloid leukemia (AML) and myelodysplastic syndrome (MDS), spanning diagnosis, prognostication, treatment prediction, and research tools. In diagnostics, deep learning applied to bone marrow smears, peripheral blood films, and flow cytometry has shown high sensitivity and specificity, outperforming conventional methods. ML-driven unsupervised clustering and consensus classification… Continue reading #Artificial #intelligence in #myeloid malignancies: Clinical applications of machine learning in myelodysplastic syndromes and acute myeloid #Leukemia
Tag: artificial-intelligence
Beyond human ears: navigating the uncharted risks of #AI scribes in clinical #practice
Artificial intelligence (AI) scribes have been rapidly adopted across health systems, driven by their promise to ease the documentation burden and reduce clinician burnout. While early evidence shows efficiency gains, this commentary cautions that adoption is outpacing validation and oversight. Without greater scrutiny, the rush to deploy AI scribes may compromise patient safety, clinical integrity,… Continue reading Beyond human ears: navigating the uncharted risks of #AI scribes in clinical #practice
The Illusion of #Readiness: Stress Testing Large Frontier Models on Multimodal #Medical Benchmarks
Large frontier models like GPT-5 now achieve top scores on medical benchmarks. But our stress tests tell a different story. Leading systems often guess correctly even when key inputs like images are removed, flip answers under trivial prompt changes, and fabricate convincing yet flawed reasoning. These aren't glitches; they expose how today's benchmarks reward test-taking… Continue reading The Illusion of #Readiness: Stress Testing Large Frontier Models on Multimodal #Medical Benchmarks
#AI -guided patient stratification improves outcomes and efficiency in the AMARANTH #Alzheimer’s Disease clinical trial
Alzheimer’s Disease (AD) drug discovery has been hampered by patient heterogeneity, and the lack of sensitive tools for precise stratification. Here, we demonstrate that our robust and interpretable AI-guided tool (predictive prognostic model, PPM) enhances precision in patient stratification, improving outcomes and decreasing sample size for a AD clinical trial. The AMARANTH trial of lanabecestat,… Continue reading #AI -guided patient stratification improves outcomes and efficiency in the AMARANTH #Alzheimer’s Disease clinical trial
Your #Brain on ChatGPT: Accumulation of #Cognitive Debt when Using an #AI Assistant for Essay Writing Task
This study explores the neural and behavioral consequences of LLM-assisted essay writing. Participants were divided into three groups: LLM, Search Engine, and Brain-only (no tools). Each completed three sessions under the same condition. In a fourth session, LLM users were reassigned to Brain-only group (LLM-to-Brain), and Brain-only users were reassigned to LLM condition (Brain-to-LLM). A… Continue reading Your #Brain on ChatGPT: Accumulation of #Cognitive Debt when Using an #AI Assistant for Essay Writing Task
Human– #AI collectives most accurately #diagnose #clinical vignettes
Large language models (LLMs) have great potential for high-stakes applications such as medical diagnostics but face challenges including hallucinations, biases, and lack of common sense. We address these limitations through a hybrid human–AI system that combines physicians’ expertise with LLMs to generate accurate differential medical diagnoses. Analyzing over 2,000 text-based medical case vignettes, hybrid collectives… Continue reading Human– #AI collectives most accurately #diagnose #clinical vignettes
Efficiency and Quality of Generative #AI–Assisted #Radiograph Reporting
Question Is clinical use of artificial intelligence (AI)–generated draft radiograph reports associated with documentation efficiency, clinical accuracy, textual quality, and ability to promptly detect pneumothorax requiring intervention?Findings In this cohort study, in 11 980 model-assisted radiograph interpretations in live clinical care, model use was associated with a 15.5% documentation efficiency improvement, with no change in radiologist-evaluated… Continue reading Efficiency and Quality of Generative #AI–Assisted #Radiograph Reporting
#Artificial #intelligence vs human #clinicians: a comparative analysis of complex medical query handling across the USA and Australia
PurposeThis study sought to explore the practical application and effectiveness of AI-generated responses in healthcare and compared these with human clinician responses to complex medical queries in the USA and Australia. The study identifies strengths and limitations of AI in clinical settings and offers insights into its potential to enhance healthcare delivery.Design/methodology/approachA comparative analysis used… Continue reading #Artificial #intelligence vs human #clinicians: a comparative analysis of complex medical query handling across the USA and Australia
Mammographic classification of interval breast cancers and #artificial intelligence performance
European studies suggest artificial intelligence (AI) can reduce interval breast cancers (IBCs). However, research on IBC classification and AI’s effectiveness in the U.S., particularly using digital breast tomosynthesis (DBT) and annual screening, is limited. We aimed to mammographically classify IBCs and assess AI performance using a 12-month screening interval.MethodsFrom digital mammography (DM) and DBT screening… Continue reading Mammographic classification of interval breast cancers and #artificial intelligence performance
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