AIMC Topic: Humans

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A machine learning approach for type 2 diabetes diagnosis and prognosis using tailored heterogeneous feature subsets.

Medical & biological engineering & computing
Type 2 diabetes (T2D) is becoming one of the leading health problems in Western societies, diminishing quality of life and consuming a significant share of healthcare resources. This study presents machine learning models for T2D diagnosis and progno...

Cross-institutional validation of a polar map-free 3D deep learning model for obstructive coronary artery disease prediction using myocardial perfusion imaging: insights into generalizability and bias.

European journal of nuclear medicine and molecular imaging
PURPOSE: Deep learning (DL) models for predicting obstructive coronary artery disease (CAD) using myocardial perfusion imaging (MPI) have shown potential for enhancing diagnostic accuracy. However, their ability to maintain consistent performance acr...

Classification of anemic condition based on photoplethysmography signals and clinical dataset.

Biomedizinische Technik. Biomedical engineering
OBJECTIVES: One of the worldwide public health issues mostly affecting children and expectant mothers is Anemia. Recently, non-invasive hemoglobin (Hb) measurements, such as machine learning (ML) algorithms, can diagnose Anemia more quickly and effic...

Machine learning prediction of effective radiation doses in various computed tomography applications: a virtual human phantom study.

Biomedizinische Technik. Biomedical engineering
OBJECTIVES: In this work, it was aimed to employ machine learning (ML) algorithms to accurately forecast the radiation doses for phantoms while accounting for the most popular CT protocols.

Nanophotonic sensors and AI for a new possible approach for accurate diagnosis of salivary glands tumors: a technical note.

Journal of cranio-maxillo-facial surgery : official publication of the European Association for Cranio-Maxillo-Facial Surgery
Currently, diagnosing salivary gland tumors in their early stages presents significant challenges. This paper aims to outline a feasibility analysis of a novel approach utilizing advanced nanophotonic sensors and AI to address these diagnostic issues...

PILOT: Deep Siamese network with hybrid attention improves prediction of mutation impact on protein stability.

Neural networks : the official journal of the International Neural Network Society
Evaluating the mutation impact on protein stability (ΔΔG) is essential in the study of protein engineering and understanding molecular mechanisms of disease-associated mutations. Here, we propose a novel deep learning framework, PILOT, for improved p...

S4-KD: A single step spiking SiamFC+ + for object tracking with knowledge distillation.

Neural networks : the official journal of the International Neural Network Society
Spiking neural networks (SNNs), which transmit information through binary spikes, have the advantages of high efficiency and low energy consumption. At present, the multiple time steps of SNNs can lead to increased latency and power consumption. To t...

A comprehensive review of computational methods for Protein-DNA binding site prediction.

Analytical biochemistry
Accurately identifying protein-DNA binding sites is essential for understanding the molecular mechanisms underlying biological processes, which in turn facilitates advancements in drug discovery and design. While biochemical experiments provide the m...

ChatGPT versus expert arthroplasty surgeons in total knee arthroplasty patient counseling.

The Knee
BACKGROUND: This study aimed to assess the effectiveness of AI compared directly with expert arthroplasty surgeons regarding patient counseling for total knee arthroplasty (TKA).

Establishing a Validation Framework of Treatment Discontinuation in Claims Data Using Natural Language Processing and Electronic Health Records.

Clinical pharmacology and therapeutics
Measuring medication discontinuation in claims data primarily relies on the gaps between prescription fills, but such definitions are rarely validated. This study aimed to establish a natural language processing (NLP)-based validation framework to ev...