Artificial Intelligence Medical Compendium

Explore the latest research on artificial intelligence and machine learning in medicine.

Showing 58,261 to 58,270 of 227,634 articles

Systematic Characterization of Minimal Deep Learning Architectures: A Unified Analysis of Convergence, Pruning, and Quantization

arXiv Jan 25, 2026
Deep learning networks excel at classification, yet identifying minimal architectures that reliably solve a task remains challenging. We present a computational methodology for systematically exploring and analyzing the relationships among convergenc... read more 
Machine Learning cs.CV

MorphXAI: An Explainable Framework for Morphological Analysis of Parasites in Blood Smear Images

arXiv Jan 25, 2026
Parasitic infections remain a pressing global health challenge, particularly in low-resource settings where diagnosis still depends on labor-intensive manual inspection of blood smears and the availability of expert domain knowledge. While deep learn... read more 
Computer Vision and Pattern Recognition

Strip-Fusion: Spatiotemporal Fusion for Multispectral Pedestrian Detection

arXiv Jan 25, 2026
Pedestrian detection is a critical task in robot perception. Multispectral modalities (visible light and thermal) can boost pedestrian detection performance by providing complementary visual information. Several gaps remain with multispectral pedestr... read more 
Computer Vision and Pattern Recognition

MlPET: A Localized Neural Network Approach for Probabilistic Post-Reconstruction PET Image Analysis Using Informed Priors

arXiv Jan 25, 2026
We develop and evaluate MlPET, a fast localized machine learning approach for probabilistic PET image analysis addressing the noise-resolution trade-off in conventional reconstructions. MlPET replaces computationally demanding Markov chain Monte Carl... read more 
Medical Physics cs.LG

Multimodal Machine Learning for Soft High-k Elastomers under Data Scarcity

arXiv Jan 25, 2026
Dielectric materials are critical building blocks for modern electronics such as sensors, actuators, and transistors. With the rapid recent advance in soft and stretchable electronics for emerging human- and robot-interfacing applications, there is a... read more 
Machine Learning cond-mat.mtrl-sci

Raman and SERS analytical platform with machine learning for classifying wild type p53 and hotspot mutants R175H and R273H.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy Jan 25, 2026
The development of analytical approaches capable of detecting subtle protein conformational changes is of significant interest in biomedicine, particularly for disease diagnostics and biomolecular characterization. In this work, the tumor suppressor ... read more 

LSWNet: A physics-informed neural network for ultrasonic wavefield prediction and elastic constant inversion in unidirectional CFRP.

Ultrasonics Jan 25, 2026
Accurate determination of elastic constants is crucial for reliable ultrasonic defect detection in carbon fiber reinforced plastic (CFRP). However, non-destructive in-situ characterization of these constants, particularly via full-waveform inversion ... read more 

Matrix-Transformation based Low-Rank Adaptation (MTLoRA): A brain-inspired method for parameter-efficient fine-tuning.

Neural networks : the official journal of the International Neural Network Society Jan 25, 2026
Parameter-efficient fine-tuning (PEFT) reduces the compute and memory demands of adapting large language models, yet standard low-rank adapters (e.g., LoRA) can lag full fine-tuning in performance and stability because they restrict updates to a fixe... read more 

Establishment of a quantitative GC-MS method for acrylamide detection and in situ kinetic study of acrylamide formation in fried potato slices.

Food chemistry Jan 25, 2026
This study established a reliable quantification technique (acrylamide derivatization and GC-MS) for acrylamide detection due to the high accuracy, reproducibility, sensitivity, and good stability. Specifically, the pre-treatment conditions of extrac... read more 

Feasibility study of fast T2-weighted imaging with deep-learning reconstruction in volunteers and emergency patients with acute abdomen.

European journal of radiology Jan 25, 2026
PURPOSE: To evaluate the image quality and clinical utility of DLR-enhanced single-shot fast spin-echo (SSFSE) T2-weighted imaging (T2WI) for diagnosing acute abdominal conditions, compared to standard SSFSE and Periodically Rotated Overlapping Paral... read more 
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