AIMC Topic: Middle Aged

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Improving Image Quality and Diagnostic Performance of CCTA in Patients with Challenging Heart Rate Conditions using a Deep Learning-based Motion Correction Algorithm.

Current medical imaging
OBJECTIVE: Challenging HR conditions, such as elevated Heart Rate (HR) and Heart Rate Variability (HRV), are major contributors to motion artifacts in Coronary Computed Tomography Angiography (CCTA). This study aims to assess the impact of a deep lea...

A Multi-Institutional Natural Language Processing Pipeline to Extract Performance Status From Electronic Health Records.

Cancer control : journal of the Moffitt Cancer Center
PURPOSE: Performance status (PS), an essential indicator of patients' functional abilities, is often documented in clinical notes of patients with cancer. The use of natural language processing (NLP) in extracting PS from electronic medical records (...

[AI based Evaluation of Psychotrauma related to Lahars in the Commune of Prêcheur in the French Antilles].

Sante mentale au Quebec
Objectives Natural disasters have a significant impact on mental health. Data collected from the population offer a unique opportunity for post-disaster monitoring to help identify psychological support needs. The aim of this study is: 1) to identify...

'Humans think outside the pixels' - Radiologists' perceptions of using artificial intelligence for breast cancer detection in mammography screening in a clinical setting.

Health informatics journal
OBJECTIVE: This study aimed to explore radiologists' views on using an artificial intelligence (AI) tool named ScreenTrustCAD with Philips equipment) as a diagnostic decision support tool in mammography screening during a clinical trial at Capio Sank...

Artificial intelligence in primary care practice: Qualitative study to understand perspectives on using AI to derive patient social data.

Canadian family physician Medecin de famille canadien
OBJECTIVE: To understand the perspectives of primary care clinicians and health system leaders on the use of artificial intelligence (AI) to derive information about patients' social determinants of health.

Machine learning model for osteoporosis diagnosis based on bone turnover markers.

Health informatics journal
To assess the diagnostic utility of bone turnover markers (BTMs) and demographic variables for identifying individuals with osteoporosis. A cross-sectional study involving 280 participants was conducted. Serum BTM values were obtained from 88 patient...

Artificial Intelligence-Generated Patient Education Materials for Helicobacter pylori Infection: A Comparative Analysis.

Helicobacter
BACKGROUND: Patient education contributes to improve public awareness of Helicobacter pylori. Large language models (LLMs) offer opportunities to revolutionize patient education transformatively. This study aimed to assess the quality of patient educ...

Prediction of early-phase cytomegalovirus pneumonia in post-stem cell transplantation using a deep learning model.

Technology and health care : official journal of the European Society for Engineering and Medicine
BACKGROUND: Diagnostic challenges exist for CMV pneumonia in post-hematopoietic stem cell transplantation (post-HSCT) patients, despite early-phase radiographic changes.

New perspectives of forensic pathology through machine learning approach on autopsy data: a pilot study.

La Clinica terapeutica
BACKGROUND: The analysis, interpretation and storage of information is entrusted to the individual expert, who bases his judgments on the knowledge resulting from the experience. The aim of this experimental study is to analyse and introduce a new li...