AIMC Topic: Humans

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Evaluation of a Task-Specific Self-Supervised Learning Framework in Digital Pathology Relative to Transfer Learning Approaches and Existing Foundation Models.

Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc
An integral stage in typical digital pathology workflows involves deriving specific features from tiles extracted from a tessellated whole-slide image. Notably, various computer vision neural network architectures, particularly the ImageNet pretraine...

Automated Identification of Heart Failure With Reduced Ejection Fraction Using Deep Learning-Based Natural Language Processing.

JACC. Heart failure
BACKGROUND: The lack of automated tools for measuring care quality limits the implementation of a national program to assess guideline-directed care in heart failure with reduced ejection fraction (HFrEF).

A look at the emerging trends of large language models in ophthalmology.

Current opinion in ophthalmology
PURPOSE OF REVIEW: As the surge in large language models (LLMs) and generative artificial intelligence (AI) applications in ophthalmology continue to expand, this review seeks to update physicians of the current progress, to catalyze further work to ...

Inter- and intra-rater reliability of cognitive assessment conducted by assistive robot for older adults living in the community: a preliminary study.

Psychogeriatrics : the official journal of the Japanese Psychogeriatric Society
BACKGROUND: The purpose of this study was to reveal inter- and intra-rater reliability of the detailed evaluation of cognitive function by assistive robot for older adults.

Machine learning-based prediction of sarcopenia in community-dwelling middle-aged and older adults: findings from the CHARLS.

Psychogeriatrics : the official journal of the Japanese Psychogeriatric Society
BACKGROUND: Sarcopenia is a prominent issue among aging populations and associated with poor health outcomes. This study aimed to examine the predictive value of questionnaire and biomarker data for sarcopenia, and to further develop a user-friendly ...

A systematic review of networks for prognostic prediction of health outcomes and diagnostic prediction of health conditions within Electronic Health Records.

Artificial intelligence in medicine
BACKGROUND AND OBJECTIVE: Using graph theory, Electronic Health Records (EHRs) can be represented graphically to exploit the relational dependencies of the multiple information formats to improve Machine Learning (ML) prediction models. In this syste...

Lung nodule classification using radiomics model trained on degraded SDCT images.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Low-dose computed tomography (LDCT) screening has shown promise in reducing lung cancer mortality; however, it suffers from high false positive rates and a scarcity of available annotated datasets. To overcome these challeng...

Automatic noise detection for ambulatory electrocardiogram in presence of ventricular arrhythmias through a machine learning approach.

Computers in biology and medicine
Noise detection in ambulatory electrocardiography is investigated as a machine learning binary classification problem on a set of twelve noise indices. Ten of these noise indices are replicated from relevant scientific literature. Two novel noise ind...

Accuracy of natural language processors for patients seeking inguinal hernia information.

Surgical endoscopy
BACKGROUND: NLPs such as ChatGPT are novel sources of online healthcare information that are readily accessible and integrated into internet search tools. The accuracy of NLP-generated responses to health information questions is unknown.

Target-specified reference-based deep learning network for joint image deblurring and resolution enhancement in surgical zoom lens camera calibration.

Computers in biology and medicine
BACKGROUND AND OBJECTIVE: For the augmented reality of surgical navigation, which overlays a 3D model of the surgical target on an image, accurate camera calibration is imperative. However, when the checkerboard images for calibration are captured us...