AIMC Topic: Male

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Deep neural networks detect suicide risk from textual facebook posts.

Scientific reports
Detection of suicide risk is a highly prioritized, yet complicated task. Five decades of research have produced predictions slightly better than chance (AUCs = 0.56-0.58). In this study, Artificial Neural Network (ANN) models were constructed to pred...

Reconstructing lost BOLD signal in individual participants using deep machine learning.

Nature communications
Signal loss in blood oxygen level-dependent (BOLD) functional neuroimaging is common and can lead to misinterpretation of findings. Here, we reconstructed compromised fMRI signal using deep machine learning. We trained a model to learn principles gov...

Characterization and wearability evaluation of a fully portable wrist exoskeleton for unsupervised training after stroke.

Journal of neuroengineering and rehabilitation
BACKGROUND: Chronic hand and wrist impairment are frequently present following stroke and severely limit independence in everyday life. The wrist orientates and stabilizes the hand before and during grasping, and is therefore of critical importance i...

Low Testosterone on Social Media: Application of Natural Language Processing to Understand Patients' Perceptions of Hypogonadism and Its Treatment.

Journal of medical Internet research
BACKGROUND: Despite the results of the Testosterone Trials, physicians remain uncomfortable treating men with hypogonadism. Discouraged, men increasingly turn to social media to discuss medical concerns.

External Validation of the Long Short-Term Memory Artificial Neural Network-Based SCaP Survival Calculator for Prediction of Prostate Cancer Survival.

Cancer research and treatment
PURPOSE: Decision-making for treatment of newly diagnosed prostate cancer (PCa) is complex due to the multiple initial treatment modalities available. We aimed to externally validate the SCaP (Severance Study Group of Prostate Cancer) Survival Calcul...

Prospective Validation of Vesical Imaging-Reporting and Data System Using a Next-Generation Magnetic Resonance Imaging Scanner-Is Denoising Deep Learning Reconstruction Useful?

The Journal of urology
PURPOSE: The Vesical Imaging Reporting and Data System (VI-RADS) was launched in 2018 to standardize reporting of magnetic resonance imaging for bladder cancer. This study aimed to prospectively validate VI-RADS using a next-generation magnetic reson...

Machine learning-based FDG PET-CT radiomics for outcome prediction in larynx and hypopharynx squamous cell carcinoma.

Clinical radiology
AIM: To determine whether machine learning-based radiomic feature analysis of baseline integrated 2-[F]-fluoro-2-deoxy-d-glucose (FDG) positron-emission tomography (PET) computed tomography (CT) predicts disease progression in patients with locally a...

Developing a Machine Learning Algorithm for Identifying Abnormal Urothelial Cells: A Feasibility Study.

Acta cytologica
INTRODUCTION: Urine cytology plays an important role in diagnosing urothelial carcinoma (UC). However, urine cytology interpretation is subjective and difficult. Morphogo (ALAB, Boston, MA, USA), equipped with automatic acquisition and scanning, opti...