AIMC Topic: Clinical Relevance
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Clinical relevance of deep learning models in predicting the onset timing of cancer pain exacerbation.
Scientific reports
Jul 17, 2023
Cancer pain is a challenging clinical problem that is encountered in the management of cancer pain. We aimed to investigate the clinical relevance of deep learning models that predict the onset of cancer pain exacerbation in hospitalized patients. We...
Clinical Relevance and Function of Anterior Talofibular Ligament Superior and Inferior Fascicles: A Robotic Study.
The American journal of sports medicine
May 26, 2023
BACKGROUND: Ankle lateral ligament sprains are common injuries in sports, and some may result in persistent ankle pain and a feeling of instability without clinical evidence of instability. The anterior talofibular ligament (ATFL) has 2 distinct fasc...
Machine Learning of Physiologic Waveforms and Electronic Health Record Data: A Large Perioperative Data Set of High-Fidelity Physiologic Waveforms.
Critical care clinics
May 18, 2023
Perioperative morbidity and mortality are significantly associated with both static and dynamic perioperative factors. The studies investigating static perioperative factors have been reported; however, there are a limited number of previous studies ...
Deep learning to refine the identification of high-quality clinical research articles from the biomedical literature: Performance evaluation.
Journal of biomedical informatics
May 8, 2023
BACKGROUND: Identifying practice-ready evidence-based journal articles in medicine is a challenge due to the sheer volume of biomedical research publications. Newer approaches to support evidence discovery apply deep learning techniques to improve th...
Automated Evaluation of Upper Airway Obstruction Based on Deep Learning.
BioMed research international
Feb 18, 2023
OBJECTIVES: This study is aimed at developing a screening tool that could evaluate the upper airway obstruction on lateral cephalograms based on deep learning.
Guidelines and evaluation of clinical explainable AI in medical image analysis.
Medical image analysis
Nov 17, 2022
Explainable artificial intelligence (XAI) is essential for enabling clinical users to get informed decision support from AI and comply with evidence-based medical practice. Applying XAI in clinical settings requires proper evaluation criteria to ensu...
Clinical significance of limited and extended pelvic lymph node dissection during robot-assisted radical prostatectomy for patients with localized prostate cancer: A retrospective, propensity score matching analysis.
International journal of urology : official journal of the Japanese Urological Association
Oct 28, 2022
OBJECTIVES: We investigated the diagnostic and therapeutic benefits of limited or extended pelvic lymph node dissection during a robot-assisted radical prostatectomy for localized prostate cancer.
Accuracy and clinical relevance of an automated, algorithm-based analysis of facial signs from selfie images of women in the United States of various ages, ancestries and phototypes: A cross-sectional observational study.
Journal of the European Academy of Dermatology and Venereology : JEADV
Sep 9, 2022
BACKGROUND: Real-life validation is necessary to ensure our artificial intelligence (AI) skin diagnostic tool is inclusive across a diverse and representative US population of various ages, ancestries and skin phototypes.
Clinical relevance of computationally derived tubular features and their spatial relationships with the interstitial microenvironment in minimal change disease/focal segmental glomerulosclerosis.
Kidney international
Aug 1, 2025
BACKGROUND: Visual scoring of tubular damage has limitations in capturing the full spectrum of structural changes and prognostic potential. Here, we investigated if computationally quantified tubular features can enhance prognostication and reveal sp...
Comparative analysis of clinical relevance and accuracy in AI-assisted patient consultations on ankle and clavicle fracture surgeries.
Injury
Jul 1, 2025
BACKGROUND: It is becoming increasingly important to evaluate the effectiveness of large language models (LLMs) and query-assisted platforms like Google and ChatGPT in providing clinically relevant and accurate information to patient-initiated inquir...
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