Hybrid CNN-Transformer AI Classifies Melanoma with 98.55% Accuracy on ISIC 2019
A hybrid CNN-Transformer framework called LHCT-Net reached 98.55% accuracy for melanoma-versus-non-melanoma classification on the 25,331-image ISIC 2019 dataset.
A hybrid CNN-Transformer framework called LHCT-Net reached 98.55% accuracy for melanoma-versus-non-melanoma classification on the 25,331-image ISIC 2019 dataset.
An AI model trained on nearly 6,000 annotated uterine ultrasound images automatically segments the endometrium, measures its thickness with sub-millimeter ...
A new open-access guide breaks the Discussion section of clinical and epidemiological papers into six purposeful elements, from summarizing findings ...
A new open-access review in Cancer Nanotechnology surveys how nanomaterials could improve colorectal cancer diagnosis, targeted therapy, and personalized theranostics.
A comparative study found that ChatGPT-4o, Claude 3.5 Sonnet, and Deepseek-R1 produced accurate, safe, fabrication-free exercise messages for older adults, ...
A ten-year bibliometric analysis of 320 articles finds artificial intelligence research on triple negative breast cancer peaked at 104 publications ...
A new Perspective in Globalization and Health proposes a five-layer AI framework and IGAD-anchored roadmap for climate-health early warning across ...
A qualitative study of 18 Danish general practitioners found cautious optimism about AI voice-to-text documentation tools, contingent on accuracy, workflow ...
A narrative review argues that surgery and rehabilitation in cerebral palsy work best when tightly coordinated, while warning that direct ...
A 2024 survey at Universidad Ricardo Palma found 92.4 percent of 278 medical students reported previous AI use for academic ...
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© 2025 Scienmag - Science Magazine