AIMC Topic: Humans

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Increased brain fractional perfusion in obesity using intravoxel incoherent motion (IVIM) MRI metrics.

Obesity (Silver Spring, Md.)
OBJECTIVE: This research seeks to shed light on the associations between brain perfusion, cognitive function, and mental health in individuals with and without obesity.

Raman spectrum combined with deep learning for precise recognition of Carbapenem-resistant Enterobacteriaceae.

Analytical and bioanalytical chemistry
Carbapenem-resistant Enterobacteriaceae (CRE) is a major pathogen that poses a serious threat to human health. Unfortunately, currently, there are no effective measures to curb its rapid development. To address this, an in-depth study on the surface-...

Generative pretrained transformer-4, an artificial intelligence text predictive model, has a high capability for passing novel written radiology exam questions.

International journal of computer assisted radiology and surgery
PURPOSE: AI-image interpretation, through convolutional neural networks, shows increasing capability within radiology. These models have achieved impressive performance in specific tasks within controlled settings, but possess inherent limitations, s...

Automatic generation of conclusions from neuroradiology MRI reports through natural language processing.

Neuroradiology
PURPOSE: The conclusion section of a radiology report is crucial for summarizing the primary radiological findings in natural language and essential for communicating results to clinicians. However, creating these summaries is time-consuming, repetit...

Distribution-Agnostic Deep Learning Enables Accurate Single-Cell Data Recovery and Transcriptional Regulation Interpretation.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)
Single-cell RNA sequencing (scRNA-seq) is a robust method for studying gene expression at the single-cell level, but accurately quantifying genetic material is often hindered by limited mRNA capture, resulting in many missing expression values. Exist...

SynerGNet: A Graph Neural Network Model to Predict Anticancer Drug Synergy.

Biomolecules
Drug combination therapy shows promise in cancer treatment by addressing drug resistance, reducing toxicity, and enhancing therapeutic efficacy. However, the intricate and dynamic nature of biological systems makes identifying potential synergistic d...

Sensory manipulation as a countermeasure to robot teleoperation delays: system and evidence.

Scientific reports
In the realm of robotics and automation, robot teleoperation, which facilitates human-machine interaction in distant or hazardous settings, has surged in significance. A persistent issue in this domain is the delays between command issuance and actio...

Robot-assisted thoracic surgery for benign tumors at the cervicothoracic junction: a propensity-matched study.

Scientific reports
This study aimed to assess the feasibility and safety of robot-assisted thoracic surgery (RATS) for resecting benign tumors of the cervicothoracic junction. Between 2017 and 2021, a total of 54 patients with benign cervicothoracic junction tumors wer...

A multimodal deep learning approach for the prediction of cognitive decline and its effectiveness in clinical trials for Alzheimer's disease.

Translational psychiatry
Alzheimer's disease is one of the most important health-care challenges in the world. For decades, numerous efforts have been made to develop therapeutics for Alzheimer's disease, but most clinical trials have failed to show significant treatment eff...

Leveraging artificial intelligence to advance implementation science: potential opportunities and cautions.

Implementation science : IS
BACKGROUND: The field of implementation science was developed to address the significant time delay between establishing an evidence-based practice and its widespread use. Although implementation science has contributed much toward bridging this gap,...