AIMC Topic: Male

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Letter to the editor: interpretable machine learning model predicts 1‑year inguinal hernia risk after robot‑assisted radical prostatectomy.

Journal of robotic surgery
We read with interest the recent article by Yu et al., "Interpretable machine learning model predicts 1-year inguinal hernia risk after robot-assisted radical prostatectomy" (DOI: 10.1007/s11701-025-02723-5) , which represents an important step in ap...

Performance of an artificial intelligence algorithm for interpreting lung sounds from children hospitalised with pneumonia in Malawi.

Journal of global health
BACKGROUND: Pneumonia is a leading cause of death in under five year olds globally. World Health Organization (WHO) pneumonia diagnostic guidelines rely on non-specific clinical findings. Lung auscultation could improve pneumonia diagnosis, but conve...

Detection and score grading for prostate adenocarcinoma using semantic segmentation.

PloS one
Prostate cancer is a major global health challenge. In this study, we present an approach for the detection and grading of prostate cancer through the semantic segmentation of adenocarcinoma tissues, specifically focusing on distinguishing between Gl...

Mortality prediction for ICU patients with mental disorders using large language models ensemble and unstructured medical notes.

PloS one
Assessing mortality risk in the intensive care unit (ICU) is crucial for improving clinical outcomes and management strategies. Conventional artificial intelligence studies often neglect vital clinical information contained in unstructured medical no...

Improving segmentation precision in prostate cancer adaptive radiation therapy with a patient-specific network.

PloS one
Adaptive radiotherapy (ART) enhances prostate cancer treatment by accounting for daily anatomical variations, but clinical implementation remains limited due to the need for accurate and efficient auto segmentation; manual corrections after automated...

Risk prediction of all-cause mortality in hospitalized patients with severe acute pancreatitis by serum urea nitrogen/albumin ratio.

PloS one
BACKGROUND: Classification of risk levels in patients with acute pancreatitis remains a difficult task. Although some biomarkers have emerged to predict the prognosis of patients with acute pancreatitis, they have not been widely used in clinical pra...

Development and validation of a machine learning-based predictive model for clinical remission in Crohn's disease patients receiving Adalimumab therapy.

PloS one
Crohn's disease (CD), a chronic inflammatory bowel disease, is witnessing a rising global incidence. Adalimumab (ADA), a biological agent, is widely used in its treatment. However, patients exhibit significant individual variability in responses to A...

Artesunate alleviates chronic allergic rhinitis and asthma syndrome via the CCR3/NF-κB pathway: a comprehensive analysis.

International immunopharmacology
BACKGROUND: Chronic allergic rhinitis and asthma syndrome (CARAS) is a comorbid inflammatory condition affecting both upper and lower airways, with limited treatment options. Artesunate (ART), a derivative of artemisinin, has shown anti-inflammatory ...

Optimized deep learning-accelerated single-breath-hold abdominal HASTE with and without fat saturation improves and accelerates abdominal imaging at 3 Tesla.

BMC medical imaging
BACKGROUND: Deep learning-accelerated single-shot turbo-spin-echo techniques (DL-HASTE) enable single-breath-hold T2-weighted abdominal imaging. However, studies evaluating the image quality of DL-HASTE with and without fat saturation (FS) remain lim...

Large Language Models' Clinical Decision-Making on When to Perform a Kidney Biopsy: Comparative Study.

Journal of medical Internet research
BACKGROUND: Artificial intelligence (AI) and large language models (LLMs) are increasing in sophistication and are being integrated into many disciplines. The potential for LLMs to augment clinical decision-making is an evolving area of research.