AIMC Topic: Humans

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Is Risk-Stratifying Patients with Colorectal Cancer Using a Deep Learning-Based Prognostic Biomarker Cost-Effective?

PharmacoEconomics
OBJECTIVES: Accurate risk stratification of patients with stage II and III colorectal cancer (CRC) prior to treatment selection enables limited health resources to be efficiently allocated to patients who are likely to benefit from adjuvant chemother...

Successful prediction of left bundle branch block-induced cardiomyopathy and treatment effect by artificial intelligence-enabled electrocardiogram.

Pacing and clinical electrophysiology : PACE
BACKGROUND: Left bundle branch block (LBBB) induced cardiomyopathy is an increasingly recognized disease entity.  However, no clinical testing has been shown to be able to predict such an occurrence.

Therapeutic endoscopy: Recent updates and future directions.

Digestive and liver disease : official journal of the Italian Society of Gastroenterology and the Italian Association for the Study of the Liver
The landscape of therapeutic endoscopy has undergone a remarkable evolution over the past few decades, carving out a niche that merges innovative technology with advanced clinical practice. As we venture further into the 21st century, the horizon of ...

Duodenal papilla radiomics-based prediction model for post-ERCP pancreatitis using machine learning: a retrospective multicohort study.

Gastrointestinal endoscopy
BACKGROUND AND AIMS: The duodenal papillae are the primary and essential pathway for ERCP, greatly determining its complexity and outcome. We investigated the association between papilla morphology and post-ERCP pancreatitis (PEP) and constructed a r...

Utilizing natural language processing and large language models in the diagnosis and prediction of infectious diseases: A systematic review.

American journal of infection control
BACKGROUND: Natural Language Processing (NLP) and Large Language Models (LLMs) hold largely untapped potential in infectious disease management. This review explores their current use and uncovers areas needing more attention.

The value of artificial intelligence for the treatment of mechanically ventilated intensive care unit patients: An early health technology assessment.

Journal of critical care
PURPOSE: The health and economic consequences of artificial intelligence (AI) systems for mechanically ventilated intensive care unit patients often remain unstudied. Early health technology assessments (HTA) can examine the potential impact of AI sy...

Assessing the Influence of B-US, CDFI, SE, and Patient Age on Predicting Molecular Subtypes in Breast Lesions Using Deep Learning Algorithms.

Journal of ultrasound in medicine : official journal of the American Institute of Ultrasound in Medicine
OBJECTIVES: Our study aims to investigate the impact of B-mode ultrasound (B-US) imaging, color Doppler flow imaging (CDFI), strain elastography (SE), and patient age on the prediction of molecular subtypes in breast lesions.

Self-paced regularized adaptive multi-view unsupervised feature selection.

Neural networks : the official journal of the International Neural Network Society
Multi-view unsupervised feature selection (MUFS) is an efficient approach for dimensional reduction of heterogeneous data. However, existing MUFS approaches mostly assign the samples the same weight, thus the diversity of samples is not utilized effi...

Anat-SFSeg: Anatomically-guided superficial fiber segmentation with point-cloud deep learning.

Medical image analysis
Diffusion magnetic resonance imaging (dMRI) tractography is a critical technique to map the brain's structural connectivity. Accurate segmentation of white matter, particularly the superficial white matter (SWM), is essential for neuroscience and cli...

Multimodal Machine Learning for Prediction of 30-Day Readmission Risk in Elderly Population.

The American journal of medicine
BACKGROUND: Readmission within 30 days is a prevalent issue among elderly patients, linked to unfavorable health outcomes. Our objective was to develop and validate multimodal machine learning models for predicting 30-day readmission risk in elderly ...