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Clinical Practice
AI assistance linked to higher malignancy detection in nurse-led skin cancer screening.
Preprint
In a real‑world evaluation of nurse‑led teledermoscopy across 577 MoleMap clinics (98,422 patients, 1,102,382 lesions), AI decision support was associated with a higher malignancy detection rate than standard screening and with more intervention and safety‑netting recommendations alongside fewer no‑action calls; findings are observational and require prospective confirmation. [2]
Medical Imaging
Radiomics‑enhanced model improves ICH prognosis prediction.
Preprint
In a retrospective multicenter study of 2,680 patients with spontaneous intracerebral hemorrhage, a model that combined radiomics features with clinical and CT variables achieved an AUC of 0.95 for prognostic risk stratification, with robust external validation AUC of 0.86, compared with 0.59 for clinical‑only models. [1]
Medical Imaging
Interview: Stockholm to use AI as one of two independent readers in mammogram screening.
Podcast from Health & Veritas
The interview says Stockholm will use Lunit’s INSIGHT MMG as one of two independent readers for screening mammograms, with any flagged case going to human consensus before recall. A prospective study of about 55,000 women showed AI plus one radiologist detected a comparable number of cancers to two radiologists. [4]
Medical Imaging
AI flags skin lesion risk factors before clinician review.
Podcast from All-In Podcast
The interview describes a workflow where an AI system flags possible skin lesion risk factors, a human clinician then reviews the flagged lesions, and expert dermatologists on staff also review the result if any concern remains after the clinician's assessment. [3]
Sources
- An automated, explainable, NCCT-based clinical decision-support system for spontaneous intracerebral hemorrhage. · medRxiv Original source
- AI-assisted nurse-led skin cancer screening in a teledermoscopy framework: a multi-site evaluation with one million lesions · medRxiv Original source
- Daniel Ek: Life After Spotify, Broken Healthcare Incentives, Catching Disease Early & AI's Potential · All-In Podcast Original source
- Learning from Your Own Health Data with Sara Riggare and Gary Wolf · Health & Veritas Original source
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