Silent brain infarctions (SBIs), affecting 20% of adults and increasing stroke risk, evade routine MRI screening. While retinal scans offer a “window to the brain,” prior AI failed to simultaneously detect SBIs and predict…
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What You Should Know:
– AISAP, an AI Point-of-Care Diagnostics company, announced a landmark field initiative in Ghana to deploy its FDA-cleared AI-powered cardiac diagnosis platform. This program directly addresses the profound challenge of healthcare…
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Potentially malignant oral lesions are visible mucosal changes with risk of progressing to squamous cell carcinoma. These lesions are currently graded as no, mild, moderate, or severe dysplasia per WHO guidelines. While widely used,…
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Radiolucent foreign body aspiration (FBA) remains diagnostically challenging due to its subtle imaging signatures on chest CT scans, often leading to delayed or missed diagnoses. We present a deep learning model integrating MedpSeg, a…
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Cardiovascular diseases remain the leading cause of death in developed countries. This study introduces deep learning ensembles for arrhythmia detection and atrial fibrillation (AF) recurrence prediction from electrocardiogram scans, supported by explainable artificial intelligence…
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Respiratory circuit events, including fluid accumulation and circuit or cuff leakage during mechanical ventilation, increase ventilator-associated event risks but often go undetected. We developed a convolutional neural network analyzing 57,296 annotated breaths (26,768 training/internal…
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Rheumatoid arthritis (RA) is a heterogeneous disease with variable symptoms, prognosis, and treatment response, necessitating refined patient classification. We applied multimodal deep learning and clustering to identify distinct RA phenotypes using baseline clinical data…
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Reading and summarizing insights from Optical Coherence Tomography (OCT) images is a routine yet time-consuming task that requires expensive time from experienced ophthalmologists. This paper introduces the Multi-label OCT Report Generation (MORG) model, a…
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Efficient and accurate identification of genetic alterations of non-small cell lung cancer is a critical diagnostic process for targeted therapies. Utilizing advanced modern deep learning is a potential solution that can accurately predict genetic…
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Pancreatic cystic neoplasms (PCN) are critical precursors for early pancreatic cancer detection, yet current diagnostic methods lack accuracy and consistency. This multicenter study developed and validated an artificial intelligence (AI)-powered CT model (PCN-AI) for…
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