BMC medical informatics and decision making
Oct 23, 2025
BACKGROUND: Traditional diagnostic methods used by neurosurgeons are limited in their ability to address complex interactions. These limitations have necessitated the use of advanced artificial intelligence approaches capable of analyzing multidimens...
Understanding the interplay between diseases and genes is crucial for gaining deeper insights into disease mechanisms and optimizing therapeutic strategies. In recent years, various computational methods have been developed to uncover potential disea...
BACKGROUND: Strabismus is a common ocular misalignment that can impair binocular vision if untreated. Conventional diagnosis and treatment rely on clinical prism diopter (PD) readings, which quantify deviation along with base direction. However, thes...
BACKGROUND: This study aims to enhance the explainability and predictive accuracy of the Random Survival Forest (RSF) algorithm in predicting stent patency risk for patients with malignant colonic obstruction.
BACKGROUND/AIMS: This study aimed to investigate whether a real-time artificial intelligence (AI)-assisted polyp detection system can improve adenoma detection rates (ADRs) in real-world colonoscopy practice.
Sepsis is a life-threatening condition resulting from a dysregulated immune response to infection, often leading to organ failure and death. Early detection is vital, as delays significantly worsen outcomes. In recent years, the integration of artifi...
Kidney stone disease is a common syndrome and a recurring one, where it bears a 50% chance of being manifested again within ten years and may lead to serious complications like ureteral obstruction and unbearable pain. If timely intervention is consi...
U-Net has gained traction in biomedical signal processing, particularly for segmenting 1D waveforms. Building on this success, we propose a U-Net-inspired architecture that integrates both 2D and 1D CNNs to effectively learn and segment gastroesophag...
Mammography is a routine imaging technique used by radiologists to detect breast lesions, such as tumors and lumps. Precise lesion detection is critical for early treatment and diagnosis planning. Lesion detection and segmentation are still problemat...
Breast cancer diagnosis via histopathology image analysis is a complex and subjective process. While deep learning has emerged as a powerful tool for automation, achieving high accuracy across diverse cancer subtypes and magnification levels remains ...
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