AIMC Topic: Humans

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Ultrafast T2-weighted MR imaging of the urinary bladder using deep learning-accelerated HASTE at 3 Tesla.

BMC medical imaging
OBJECTIVE: This prospective study aimed to assess the feasibility of a half-Fourier single-shot turbo spin echo sequence (HASTE) with deep learning (DL) reconstruction for ultrafast imaging of the bladder with reduced susceptibility to motion artifac...

Domain-incremental white blood cell classification with privacy-aware continual learning.

Scientific reports
White blood cell (WBC) classification plays a vital role in hematology for diagnosing various medical conditions. However, it faces significant challenges due to domain shifts caused by variations in sample sources (e.g., blood or bone marrow) and di...

A hybrid fog-edge computing architecture for real-time health monitoring in IoMT systems with optimized latency and threat resilience.

Scientific reports
The advancement of the Internet of Medical Things (IoMT) has transformed healthcare delivery by enabling real-time health monitoring. However, it introduces critical challenges related to latency and, more importantly, the secure handling of sensitiv...

Integrating vision transformer-based deep learning model with kernel extreme learning machine for non-invasive diagnosis of neonatal jaundice using biomedical images.

Scientific reports
Birth complications, particularly jaundice, are one of the leading causes of adolescent death and disease all over the globe. The main severity of these illnesses may diminish if scholars study more about their sources and progress toward effective t...

An efficient deep learning based approach for automated identification of cervical vertebrae fracture as a clinical support aid.

Scientific reports
Cervical vertebrae fractures pose a significant risk to a patient's health. The accurate diagnosis and prompt treatment need to be provided for effective treatment. Moreover, the automated analysis of the cervical vertebrae fracture is of utmost impo...

Predicting clozapine-induced adverse drug reaction biomarkers using machine learning.

Scientific reports
Clozapine is an atypical antipsychotic used for patients with treatment-resistant schizophrenia. This drug has serious adverse drug reactions (ADRs), including the risk of severe neutropenia (agranulocytosis). Patients who could benefit from clozapin...

Advanced finite segmentation model with hybrid classifier learning for high-precision brain tumor delineation in PET imaging.

Scientific reports
Brain tumor segmentation plays a crucial role in clinical diagnostics and treatment planning, yet accurate and efficient segmentation remains a significant challenge due to complex tumor structures and variations in imaging modalities. Multi-feature ...

Prediction of pathogenic mutations in human transmembrane proteins and their associated diseases via utilizing pre-trained Bio-LLMs.

Communications biology
Missense mutations can disrupt the structure and function of membrane proteins, potentially impairing key biological processes and leading to various human diseases. However, existing computational methods primarily focus on binary pathogenicity clas...

Predicting New York Heart Association (NYHA) heart failure classification from medical student notes following simulated patient encounters.

Scientific reports
Random forest models have demonstrated utility in the determination of New York Heart Association (NYHA) Heart Failure Classifications. This study aims to determine the prediction accuracy of a random forest model to derive NYHA Classification from m...

Fetal-Net: enhancing Maternal-Fetal ultrasound interpretation through Multi-Scale convolutional neural networks and Transformers.

Scientific reports
Ultrasound imaging plays an important role in fetal growth and maternal-fetal health evaluation, but due to the complicated anatomy of the fetus and image quality fluctuation, its interpretation is quite challenging. Although deep learning include Co...