AIMC Topic: Humans

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Predicting Patient Demographics From Chest Radiographs With Deep Learning.

Journal of the American College of Radiology : JACR
BACKGROUND: Deep learning models are increasingly informing medical decision making, for instance, in the detection of acute intracranial hemorrhage and pulmonary embolism. However, many models are trained on medical image databases that poorly repre...

Nested epistasis enhancer networks for robust genome regulation.

Science (New York, N.Y.)
Mammalian genomes have multiple enhancers spanning an ultralong distance (>megabases) to modulate important genes, but it is unclear how these enhancers coordinate to achieve this task. We combine multiplexed CRISPRi screening with machine learning t...

A clinical decision support system optimising adjuvant chemotherapy for colorectal cancers by integrating deep learning and pathological staging markers: a development and validation study.

The Lancet. Oncology
BACKGROUND: The DoMore-v1-CRC marker was recently developed using deep learning and conventional haematoxylin and eosin-stained tissue sections, and was observed to outperform established molecular and morphological markers of patient outcome after p...

The Leaf Clinical Trials Corpus: a new resource for query generation from clinical trial eligibility criteria.

Scientific data
Identifying cohorts of patients based on eligibility criteria such as medical conditions, procedures, and medication use is critical to recruitment for clinical trials. Such criteria are often most naturally described in free-text, using language fam...

Evaluation of auto-segmentation for EBRT planning structures using deep learning-based workflow on cervical cancer.

Scientific reports
Deep learning (DL) based approach aims to construct a full workflow solution for cervical cancer with external beam radiation therapy (EBRT) and brachytherapy (BT). The purpose of this study was to evaluate the accuracy of EBRT planning structures de...

Deep learning prediction of chemical-induced dose-dependent and context-specific multiplex phenotype responses and its application to personalized alzheimer's disease drug repurposing.

PLoS computational biology
Predictive modeling of drug-induced gene expressions is a powerful tool for phenotype-based compound screening and drug repurposing. State-of-the-art machine learning methods use a small number of fixed cell lines as a surrogate for predicting actual...

Masked Joint Bilateral Filtering via Deep Image Prior for Digital X-Ray Image Denoising.

IEEE journal of biomedical and health informatics
Medical image denoising faces great challenges. Although deep learning methods have shown great potential, their efficiency is severely affected by millions of trainable parameters. The non-linearity of neural networks also makes them difficult to be...

iCVM: An Interpretable Deep Learning Model for CVM Assessment Under Label Uncertainty.

IEEE journal of biomedical and health informatics
The Cervical Vertebral Maturation (CVM) method aims to determine the craniofacial skeletal maturational stage, which is crucial for orthodontic and orthopedic treatment. In this paper, we explore the potential of deep learning for automatic CVM asses...

Deep Features Aggregation-Based Joint Segmentation of Cytoplasm and Nuclei in White Blood Cells.

IEEE journal of biomedical and health informatics
White blood cells (WBCs), also known as leukocytes, are one of the valuable parts of the blood and immune system. Typically, pathologists use microscope for the manual inspection of blood smears which is a time-consuming, error-prone, and labor-inten...

A Home-based Tele-rehabilitation System With Enhanced Therapist-patient Remote Interaction: A Feasibility Study.

IEEE journal of biomedical and health informatics
As a promising alternative to hospital-based manual therapy, robot-assisted tele-rehabilitation therapy has shown significant benefits in reducing the therapist's workload and accelerating the patient's recovery process. However, existing telerobotic...