Artificial Intelligence Medical Compendium

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

Showing 54,051 to 54,060 of 225,930 articles

Risk stratification in diabetic kidney disease: a review of prediction models for methodological advances and clinical application.

Journal of translational medicine
BACKGROUND: Diabetic kidney disease (DKD) represents the leading cause of end-stage renal disease (ESRD) worldwide, characterized by a complex pathophysiology and heterogeneous progression. Accurate prediction of the onset, progression, and adverse o... read more 

UniSyn: a multi-modal framework with knowledge transfer for anti-cancer drug synergy prediction.

Genome biology
Drug combinations can improve cancer therapy by boosting efficacy, limiting dose-related toxicity, and delaying resistance. We present UniSyn, an interpretable multi-modal deep learning framework that transfers knowledge from monotherapy responses to... read more 

Multiple weak biases support adaptive choices without prior experience: a self-supervised strategy.

Proceedings. Biological sciences
From social interaction to foraging, the survival of newborn animals depends on their ability to make adaptive decisions without prior experience. While ethological research focused on strong innate biases, recent empirical evidence shows that early ... read more 

Accessibility drives research efforts on Amazonian sarcosaprophagous flies.

Proceedings. Biological sciences
The tropics hold most of the planet's biodiversity but face significant knowledge gaps. This is particularly concerning in the Brazilian Amazon, where anthropogenic disturbances are driving species loss. Our study focused on sarcosaprophagous flies, ... read more 

Epileptic Seizure Detection from EEG Signals with Long Short-Term Memory-Transformer and Self-Supervised Learning.

International journal of neural systems
Electroencephalogram (EEG) plays a vital role in seizure detection, yet existing methods often fail to adequately capture the spatiotemporal characteristics of EEG signals, leading to limited performance. Moreover, most current models depend on super... read more 

Region-resolved proteomic map of the human brain: functional interconnections and neurological implications.

Signal transduction and targeted therapy
While progress has been made in transcriptomic profiling of the human brain, functional characterization of brain regions and their interactions on the basis of regional protein expression remains limited. Here, we constructed a proteomic map from th... read more 

Generalisation of automatic tumour segmentation in histopathological whole-slide images across multiple cancer types.

NPJ precision oncology
Deep learning is expected to aid pathologists in tasks such as tumour segmentation. We developed a general tumour segmentation model for histopathological images and examined its performance in different cancer types. The model was developed using ov... read more 

Analysis of the generalization ability of graph neural networks in cross-subject EEG emotion recognition.

Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology
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Deep Learning-based Assessment of Eyelid and Periorbital Parameters: Assisting Diagnosis and Treatment Planning in Blepharoptosis.

Journal of medical systems
Blepharoptosis is a common eyelid disorder that impairs both vision and appearance, requiring accurate assessment for effective treatment. This study aimed to develop and evaluate a deep learning (DL)-based system for automatic measurement of eyelid ... read more 

PRDX6 as a Ferroptosis-Related Hub Gene in the Entorhinal Cortex of Alzheimer's Disease: A Multidimensional Bioinformatics and Experimental Validation Study.

Journal of molecular neuroscience : MN
Ferroptosis, an iron-dependent regulated cell death form, is a key pathogenic mechanism in Alzheimer's disease (AD), especially in the entorhinal cortex, a brain region selectively vulnerable to early AD neuropathology. This study aimed to identify p... read more