AIMC Topic: Male

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Machine learning in personalized laryngeal cancer management: insights into clinical characteristics, therapeutic options, and survival predictions.

European archives of oto-rhino-laryngology : official journal of the European Federation of Oto-Rhino-Laryngological Societies (EUFOS) : affiliated with the German Society for Oto-Rhino-Laryngology - Head and Neck Surgery
PURPOSE: Over the last 40 years, there has been an unusual trend where, even though there are more varied treatments, survival rates have not improved much. Our study used survival analysis and machine learning (ML) to investigate this odd situation ...

Volumetric Artificial Intelligence Analysis of Prerupture and Postrupture Cerebral Aneurysms: Assessment of Morphologic Change.

World neurosurgery
BACKGROUND: Cerebral aneurysm rupture is a major cause of potential years of life lost. Research on rupture risk has often compared unruptured and ruptured aneurysms, with the implicit assumption that the rupture event does not significantly change a...

Artificial intelligence-enabled discovery of a RIPK3 inhibitor with neuroprotective effects in an acute glaucoma mouse model.

Chinese medical journal
BACKGROUND: Retinal ganglion cell (RGC) death caused by acute ocular hypertension is an important characteristic of acute glaucoma. Receptor-interacting protein kinase 3 (RIPK3) that mediates necroptosis is a potential therapeutic target for RGC deat...

Real-Time Freezing of Gait Prediction and Detection in Parkinson's Disease.

Sensors (Basel, Switzerland)
Freezing of gait (FOG) is a walking disturbance that can lead to postural instability, falling, and decreased mobility in people with Parkinson's disease. This research used machine learning to predict and detect FOG episodes from plantar-pressure da...

Automated Measurement of Effective Radiation Dose by F-Fluorodeoxyglucose Positron Emission Tomography/Computed Tomography.

Tomography (Ann Arbor, Mich.)
BACKGROUND/OBJECTIVES: Calculating the radiation dose from CT in F-PET/CT examinations poses a significant challenge. The objective of this study is to develop a deep learning-based automated program that standardizes the measurement of radiation dos...

Machine learning approach and geospatial analysis to determine HIV infection, awareness status, and transmission knowledge among adults in Sub-Saharan Africa.

BMC research notes
BACKGROUND: HIV/AIDS remains a major public health challenge, in Sub-Saharan Africa (SSA). In 2020, 16% of people living with HIV did not know their HIV status in SSA. Understanding the geospatial distribution of HIV infection, awareness status, and ...

Assessment of MGMT promoter methylation status in glioblastoma using deep learning features from multi-sequence MRI of intratumoral and peritumoral regions.

Cancer imaging : the official publication of the International Cancer Imaging Society
OBJECTIVE: This study aims to evaluate the effectiveness of deep learning features derived from multi-sequence magnetic resonance imaging (MRI) in determining the O-methylguanine-DNA methyltransferase (MGMT) promoter methylation status among glioblas...

Machine-learning based prediction of appendicitis for patients presenting with acute abdominal pain at the emergency department.

World journal of emergency surgery : WJES
BACKGROUND: Acute abdominal pain (AAP) constitutes 5-10% of all emergency department (ED) visits, with appendicitis being a prevalent AAP etiology often necessitating surgical intervention. The variability in AAP symptoms and causes, combined with th...

Multi-branch CNNFormer: a novel framework for predicting prostate cancer response to hormonal therapy.

Biomedical engineering online
PURPOSE: This study aims to accurately predict the effects of hormonal therapy on prostate cancer (PC) lesions by integrating multi-modality magnetic resonance imaging (MRI) and the clinical marker prostate-specific antigen (PSA). It addresses the li...