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Multi-view deep learning framework for the detection of chest X-rays compatible with pediatric pulmonary tuberculosis.

Nature communications
Tuberculosis (TB) remains a major global health burden, particularly in low-resource, high-prevalence regions. Pediatric TB diagnosis poses challenges with non-specific symptoms and less distinct radiological manifestations than adult TB. Many affect...

Robotic surgical nurses' perceptions of artificial intelligence: a qualitative study.

Journal of robotic surgery
AIM: This study aimed to explore robotic surgical nurses' perceptions and experiences of artificial intelligence (AI) and to reveal their views on its impact on professional roles and care processes.

Current utility of artificial intelligence in benign prostate surgery: a review of literature on behalf of the EAU section of endourology.

World journal of urology
OBJECTIVE: Artificial intelligence (AI) and its subsects, such as machine learning (ML) and virtual reality (VR) are subject to great interest from the urological community, and gaining space in the surgical treatment of benign prostatic hyperplasia ...

Deep learning-based vessel and nerve recognition model for lateral lymph node dissection: a retrospective feasibility study.

Langenbeck's archives of surgery
PURPOSE: Lateral lymph node dissection for rectal cancer is challenging because of the presence of blood vessels and nerves essential for postoperative genitourinary function and leg movements. Identifying these structures during surgery is crucial. ...

Universal Atrial Fibrillation Screening Using Electrocardiographic Artificial Intelligence: A Cost-Effective Approach in Rural Communities.

Journal of medical systems
Atrial fibrillation (AF) significantly contributes to the incidence of strokes. Screening for AF enhances its detection and effective management. However, universal AF screening in rural areas poses a challenge. This study evaluates the cost-effectiv...

Evaluation of postoperative bleeding risk after dental extractions in patients on antithrombotic medication: A comparison of machine learning and clinical experience.

Clinical oral investigations
OBJECTIVES: The aim of this study was to identify high-risk dental extractions in patients taking antiplatelet (AP) medication or anticoagulants (ACs) and to compare an experienced surgeon's decisions with machine learning (ML) algorithms.

Detection of cognitive load using EEG signal and lifting wavelet transform with specific lead selection.

Biomedical physics & engineering express
Solving an arithmetic task is a complex assignment that includes sequencing, memory, fact retrieval, and decision making. Observation of the human brain's response to such activities is quite essential as it helps in the diagnosis of various diseases...

Neglected brucellosis in pediatric populations from non-endemic regions: Clinical manifestations and prediction of severe disease in Yunnan Province, China.

PLoS neglected tropical diseases
BACKGROUND: Although Yunnan Province is not an endemic region for brucellosis, the disease remains a diagnostic and therapeutic challenge in children due to its atypical clinical manifestations and potential for severe complications.

Stylometry can reveal artificial intelligence authorship, but humans struggle: A comparison of human and seven large language models in Japanese.

PloS one
The purpose of this study was to estimate the artificial intelligence (AI) detection potential using stylometric analysis in Study 1 and examine the AI detection abilities of humans in Study 2. In Study 1, we compared 100 human-written public comment...

Use of machine learning for early prediction of short-term mortality in veterans with metabolic dysfunction-associated steatotic liver disease.

PloS one
BACKGROUND: Metabolic dysfunction associated steatotic liver disease (MASLD) is a leading cause of chronic liver disease worldwide and affects >25% in the United States population. We hypothesized that clinical features present in electronic health r...