AIMC Topic: Humans

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Predicting high-risk factors for postoperative inadequate analgesia and adverse reactions in cesarean delivery surgery: a prospective study.

International journal of surgery (London, England)
BACKGROUND: Early identification of high-risk factors for inadequate analgesia and adverse reactions in obstetric patients is critical for improving outcomes. This study developed a machine learning model to predict these factors and optimize anesthe...

Radiomics across modalities: a comprehensive review of neurodegenerative diseases.

Clinical radiology
Radiomics allows extraction from medical images of quantitative features that are able to reveal tissue patterns that are generally invisible to human observers. Despite the challenges in visually interpreting radiomic features and the computational ...

Machine learning approaches for real-time ZIP code and county-level estimation of state-wide infectious disease hospitalizations using local health system data.

Epidemics
The lack of conventional methods of estimating real-time infectious disease burden in granular regions inhibits timely and efficient public health response. Comprehensive data sources (e.g., state health department data) typically needed for such est...

An extension to the OVH concept for knowledge-based dose volume histogram prediction in lung tumor volumetric-modulated arc therapy.

Journal of applied clinical medical physics
PURPOSE: Volumetric-modulated arc therapy (VMAT) treatment planning allows a compromise between a sufficient coverage of the planning target volume (PTV) and a simultaneous sparing of organs-at-risk (OARs). Particularly in the case of lung tumors, de...

A Tc1- and Th1-T-lymphocyte-rich tumor microenvironment is a hallmark of MSI colorectal cancer.

The Journal of pathology
Microsatellite instability is a strong predictor of response to immune checkpoint therapy and patient outcome in colorectal cancer. Although enrichment of distinct T-cell subpopulations has been determined to impact the response to immune checkpoint ...

Clinical implementation of AI-based screening for risk for opioid use disorder in hospitalized adults.

Nature medicine
Adults with opioid use disorder (OUD) are at increased risk for opioid-related complications and repeated hospital admissions. Routine screening for patients at risk for an OUD to prevent complications is not standard practice in many hospitals, lead...

Multimodal imaging platform for enhanced tumor resection in neurosurgery: integrating hyperspectral and pCLE technologies.

International journal of computer assisted radiology and surgery
PURPOSE: This work presents a novel multimodal imaging platform that integrates hyperspectral imaging (HSI) and probe-based confocal laser endomicroscopy (pCLE) for improved brain tumor identification during neurosurgery. By combining these two modal...

Predicting cell cycle stage from 3D single-cell nuclear-stained images.

Life science alliance
The cell cycle governs the proliferation of all eukaryotic cells. Profiling cell cycle dynamics is therefore central to basic and biomedical research. However, current approaches to cell cycle profiling involve complex interventions that may confound...

Reinforcement learning for safe autonomous two-device navigation of cerebral vessels in mechanical thrombectomy.

International journal of computer assisted radiology and surgery
PURPOSE: Autonomous systems in mechanical thrombectomy (MT) hold promise for reducing procedure times, minimizing radiation exposure, and enhancing patient safety. However, current reinforcement learning (RL) methods only reach the carotid arteries, ...

A Novel Theranostic Strategy for Malignant Pulmonary Nodules by Targeted CECAM6 with Zr/I-Labeled Tinurilimab.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)
Lung adenocarcinoma (LUAD) constitutes a major cause of cancer-related fatalities worldwide. Early identification of malignant pulmonary nodules constitutes the most effective approach to reducing the mortality of LUAD. Despite the wide application o...