AIMC Topic: Reproducibility of Results
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TIRADS-based artificial intelligence systems for ultrasound images of thyroid nodules: protocol for a systematic review.
Journal of ultrasound
Nov 20, 2024
PURPOSE: The thyroid imaging reporting and data system (TIRADS) was developed as a standard global term to describe thyroid nodule risk features, aiming to address issues such as variability and low reproducibility in nodule feature detection and int...
Perioperative risk scores: prediction, pitfalls, and progress.
Current opinion in anaesthesiology
Nov 20, 2024
PURPOSE OF REVIEW: Perioperative risk scores aim to risk-stratify patients to guide their evaluation and management. Several scores are established in clinical practice, but often do not generalize well to new data and require ongoing updates to impr...
Machine Learning Algorithms Exceed Comorbidity Indices in Prediction of Short-Term Complications After Hip Fracture Surgery.
The Journal of the American Academy of Orthopaedic Surgeons
Nov 19, 2024
BACKGROUND: Hip fractures are among the most morbid acute orthopaedic injuries often due to accompanying patient frailty. The purpose of this study was to determine the reliability of assessing surgical risk after hip fracture through machine learnin...
Model Based on Ultrasound Radiomics and Machine Learning to Preoperative Differentiation of Follicular Thyroid Neoplasm.
Journal of ultrasound in medicine : official journal of the American Institute of Ultrasound in Medicine
Nov 18, 2024
OBJECTIVES: To evaluate the value of radiomics based on ultrasonography in differentiating follicular thyroid carcinoma (FTC) and follicular thyroid adenoma (FTA) and construct a tool for preoperative noninvasive predicting FTC and FTA.
Generating and evaluating synthetic data in digital pathology through diffusion models.
Scientific reports
Nov 18, 2024
Synthetic data is becoming a valuable tool for computational pathologists, aiding in tasks like data augmentation and addressing data scarcity and privacy. However, its use necessitates careful planning and evaluation to prevent the creation of clini...
Natural Language Processing to Adjudicate Heart Failure Hospitalizations in Global Clinical Trials.
Circulation. Heart failure
Nov 16, 2024
BACKGROUND: Medical record review by a physician clinical events committee is the gold standard for identifying cardiovascular outcomes in clinical trials, but is labor-intensive and poorly reproducible. Automated outcome adjudication by artificial i...
Repeatability of Microperimetry in Areas of Retinal Pigment Epithelium and Photoreceptor Loss in Geographic Atrophy Supported by Artificial Intelligence-Based Optical Coherence Tomography Biomarker Quantification.
American journal of ophthalmology
Nov 14, 2024
PURPOSE: Growing interest in microperimetry (MP) or fundus-controlled perimetry as a targeted psychometric testing method in geographic atrophy (GA) is warranted because of the disease subclinical/extrafoveal appearance or preexisting foveal loss wit...
Exploring ChatGPT's potential in ECG interpretation and outcome prediction in emergency department.
The American journal of emergency medicine
Nov 14, 2024
BACKGROUND: Approximately 20 % of emergency department (ED) visits involve cardiovascular symptoms. While ECGs are crucial for diagnosing serious conditions, interpretation accuracy varies among emergency physicians. Artificial intelligence (AI), suc...
Prognostic Significance and Associations of Neural Network-Derived Electrocardiographic Features.
Circulation. Cardiovascular quality and outcomes
Nov 14, 2024
BACKGROUND: Subtle, prognostically important ECG features may not be apparent to physicians. In the course of supervised machine learning, thousands of ECG features are identified. These are not limited to conventional ECG parameters and morphology. ...
Human identification via digital palatal scans: a machine learning validation pilot study.
BMC oral health
Nov 14, 2024
BACKGROUND: This study aims to validate a machine learning algorithm previously developed in a training population on a different randomly chosen population (i.e., test set). The discrimination potential of the palatal intraoral scan-based geometric ...
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