AIMC Topic: Humans

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A novel approach in cancer diagnosis: integrating holography microscopic medical imaging and deep learning techniques-challenges and future trends.

Biomedical physics & engineering express
Medical imaging is pivotal in early disease diagnosis, providing essential insights that enable timely and accurate detection of health anomalies. Traditional imaging techniques, such as Magnetic Resonance Imaging (MRI), Computer Tomography (CT), ult...

Interpretable machine learning and radiomics in hip MRI diagnostics: comparing ONFH and OA predictions to experts.

Frontiers in immunology
PURPOSE: Distinguishing between Osteonecrosis of the femoral head (ONFH) and Osteoarthritis (OA) can be subjective and vary between users with different backgrounds and expertise. This study aimed to construct and evaluate several Radiomics-based mac...

The calcitron: A simple neuron model that implements many learning rules via the calcium control hypothesis.

PLoS computational biology
Theoretical neuroscientists and machine learning researchers have proposed a variety of learning rules to enable artificial neural networks to effectively perform both supervised and unsupervised learning tasks. It is not always clear, however, how t...

Accuracy of latest large language models in answering multiple choice questions in dentistry: A comparative study.

PloS one
OBJECTIVES: This study aims to evaluate the performance of the latest large language models (LLMs) in answering dental multiple choice questions (MCQs), including both text-based and image-based questions.

Neuro-computational simulation of blood flow loaded with gold and maghemite nanoparticles inside an electromagnetic microchannel under rapid and unexpected change in pressure gradient.

Electromagnetic biology and medicine
In cardiovascular research, electromagnetic fields generated by Riga plates are utilized to study or manipulate blood flow dynamics, which is particularly crucial in developing treatments for conditions such as arterial plaque deposition and understa...

Automatic segmentation of the midfacial bone surface from ultrasound images using deep learning methods.

International journal of oral and maxillofacial surgery
With developments in computer science and technology, great progress has been made in three-dimensional (3D) ultrasound. Recently, ultrasound-based 3D bone modelling has attracted much attention, and its accuracy has been studied for the femur, tibia...

Intraindividual Comparison of Image Quality Between Low-Dose and Ultra-Low-Dose Abdominal CT With Deep Learning Reconstruction and Standard-Dose Abdominal CT Using Dual-Split Scan.

Investigative radiology
OBJECTIVE: The aim of this study was to intraindividually compare the conspicuity of focal liver lesions (FLLs) between low- and ultra-low-dose computed tomography (CT) with deep learning reconstruction (DLR) and standard-dose CT with model-based ite...

From errors to excellence: the pre-analytical journey to improved quality in diagnostics. A scoping review.

Clinical chemistry and laboratory medicine
This scoping review focuses on the evolution of pre-analytical errors (PAEs) in medical laboratories, a critical area with significant implications for patient care, healthcare costs, hospital length of stay, and operational efficiency. The Covidence...

Adaptive Multi-Kernel Graph Neural Network for Drug-Drug Interaction Prediction.

Interdisciplinary sciences, computational life sciences
 Combination therapy, which synergistically enhances treatment efficacy and inhibits disease progression through the combined effects of multiple drugs, has emerged as a mainstream approach for treating complex diseases and alleviating symptoms. Howe...

TDAG: A multi-agent framework based on dynamic Task Decomposition and Agent Generation.

Neural networks : the official journal of the International Neural Network Society
The emergence of Large Language Models (LLMs) like ChatGPT has inspired the development of LLM-based agents capable of addressing complex, real-world tasks. However, these agents often struggle during task execution due to methodological constraints,...