Artificial Intelligence Medical Compendium

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

Showing 37,881 to 37,890 of 223,469 articles

Supernetwork-based efficient mapping of deep learning applications to mixed-precision hardware using model adaptation.

Nature communications
The rapid proliferation of Artificial Intelligence applications necessitates scalable solutions that perform efficiently under real-world constraints. Heterogeneous accelerators combining specialized analog and digital units offer localized, energy-e... read more 

Multimodal and Hyperspectral Dataset for Segmentation of Bulky Waste using VIS, IR, NIR, and Terahertz Imaging.

Scientific data
This study presents an annotated multi-sensor, multimodal, and hyperspectral dataset designed to support deep learning-based classification and segmentation of bulky waste. The dataset comprises four distinct sensor modalities: high-resolution visibl... read more 

KM-DBSCAN: an enhanced density and centroid based border detection framework for data reduction towards green AI.

Scientific reports
Green AI aims to design and train machine learning models while taking into consideration sustainable resource usage without sacrificing model efficiency. The exponential growth of training data has led to results in increasing computational cost and... read more 

A novel superpixel based Vision Transformer for improving interpretability in glaucoma screening.

Scientific reports
Interpretability remains one of the major challenges in the clinical adoption of deep learning models for medical image analysis. In ophthalmology, particularly for glaucoma screening, explainable artificial intelligence (XAI) methods are essential f... read more 

A physics-informed machine learning framework for predicting and mitigating doxorubicin nanocarrier toxicity in normal cells.

Scientific reports
The clinical utility of doxorubicin (DOX) has been widely hampered by a dose-dependent systemic toxicity, in particular cardiotoxicity. While nanocarrier systems represent encouraging solutions, their optimization is not an easy task due to complex, ... read more 

Keeping up with the regions: a hybrid machine learning framework for estimating regional input-output tables.

Scientific reports
Accurate regional input-output (IO) tables are indispensable for economic analysis and policy-making, yet their availability remains limited due to data constraints. This paper develops a novel hybrid framework combining Generative Adversarial Networ... read more