AIMC Topic: Deep Learning

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SHIFT-DRP: Dynamic Multi-Scale Active Learning for Drug Response Prediction.

Journal of chemical information and modeling
Deep learning models show promise for drug response prediction in personalized cancer treatment, but exhibit limited prediction capability for novel drug-cell line combinations due to insufficient coverage of the chemical spaces in training data. The...

Segmentation of plateau zokor mounds in alpine meadows from UAV images using an improved UNet network.

Scientific reports
Plateau zokor mounds, created by the burrowing activity of Plateau zokor, cause significant damage to crops, grasslands, and infrastructure, particularly in the alpine meadows of the Tibetan Plateau. Traditional field surveys are inefficient and labo...

An integration of deep learning models for effective classification of human activity patterns in disabled people using gesture analysis.

Scientific reports
Human activity recognition (HAR) has numerous applications due to its widespread use of procurement tools, such as smartphones and video cameras, and its ability to capture data on human activity. HAR became a hot scientific area in the computer visi...

An intelligent framework for visually impaired people through indoor object Detection-Based assistive system using YOLO with recurrent neural networks.

Scientific reports
Vision is a fundamental sense that profoundly impacts daily life and independence. For visually impaired people (VIP), the absence or impairment of this sense presents significant challenges, particularly in navigating their environment and identifyi...

Large-scale modeling of axonal dynamic responses via deep learning.

Biomechanics and modeling in mechanobiology
Large-scale axonal dynamic simulation is critical to study white matter injury but is prohibitive in computational cost. We solve this challenge by training a convolutional neural network (CNN) that takes fiber strain profiles as inputs to instantly ...

An Interpretable Hybrid AI Model for Breast Fine Needle Aspiration Cytology Image Classification.

Journal of medical systems
While Fine needle aspiration cytology (FNAC) and mammography are both used to diagnose breast lesions, FNAC is generally more accurate than mammograms for predicting breast cancer. It is also gaining popularity as an early detection tool due to its r...

Evaluating the clinical readiness of artificial intelligence in EEG-based epilepsy diagnosis.

Journal of neural engineering
Automated electroencephalography (EEG)-based epilepsy diagnosis has reported near-perfect accuracies for almost two decades on a benchmark dataset, yet virtually no system is used in routine care. We critically re-examined this translation gap by rep...

Lightweight deep learning models for EEG decoding: a review.

Journal of neural engineering
Brain-computer interface (BCI) technology enables direct communication between the human brain and external devices by decoding electroencephalography (EEG)signals into actionable commands. As a noninvasive and portable modality, EEG-based BCIs hold ...

Fast operating room scattered radiation calculation in x-ray guided interventions by using deep learning.

Journal of radiological protection : official journal of the Society for Radiological Protection
Protecting medical personnel from the harmful effects of scattered ionising radiation during x-ray-guided procedures is a critical concern. Due to the complex and invisible nature of x-rays, monitoring radiation exposure has been challenging. Existin...

Scout-Dose-TCM: direct and prospective scout-based estimation of personalized organ and effective doses from tube current modulated CT exams.

Physics in medicine and biology
This study proposes Scout-Dose-TCM for direct, prospective estimation of organ-level and effective doses under tube current modulation (TCM) and compares its performance with two established methods.Contrast-enhanced chest-abdomen-pelvis CT exams fro...