AIMC Topic: Male

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A Novel Approach to Predict Brain Cancerous Tumor Using Transfer Learning.

Computational and mathematical methods in medicine
As the most prevalent and deadly malignancy, brain tumors have a dismal survival rate when they are at their most hazardous. Using mostly traditional medical image processing methods, segmenting and classifying brain malignant tumors is a challenging...

Intraoperative workload during robotic radical prostatectomy: Comparison between multi-port da Vinci Xi and single port da Vinci SP robots.

Applied ergonomics
The goal of this study was to quantify and compare prospective self-reported intraoperative workload and teamwork during robot-assisted radical prostatectomy (RARP) for multi-port da Vinci Xi (MP) and single-port da Vinci SP (SP) robots. The self-rep...

Deep learning-based quantitative susceptibility mapping (QSM) in the presence of fat using synthetically generated multi-echo phase training data.

Magnetic resonance in medicine
PURPOSE: To enable a fast and automatic deep learning-based QSM reconstruction of tissues with diverse chemical shifts, relevant to most regions outside the brain.

Multicentric experience in Retzius-sparing robot-assisted radical prostatectomy performed by expert surgeons for high-risk prostate cancer.

Minerva urology and nephrology
BACKGROUND: The study aim was to report the results of Retzius-Sparing robot-assisted radical Prostatectomy (RSP) in high-risk prostate cancer (HR-PCa) patients in a multicentric setting of expert surgeons and to analyze predictors of positive surgic...

Combined artificial intelligence and radiologist model for predicting rectal cancer treatment response from magnetic resonance imaging: an external validation study.

Abdominal radiology (New York)
PURPOSE: To evaluate an MRI-based radiomic texture classifier alone and combined with radiologist qualitative assessment in predicting pathological complete response (pCR) using restaging MRI with internal training and external validation.

Prediction Performance of Deep Learning for Colon Cancer Survival Prediction on SEER Data.

BioMed research international
Colon and rectal cancers are the most common kinds of cancer globally. Colon cancer is more prevalent in men than in women. Early detection increases the likelihood of survival, and treatment significantly increases the likelihood of eradicating the ...

The Acoustic Dissection of Cough: Diving Into Machine Listening-based COVID-19 Analysis and Detection.

Journal of voice : official journal of the Voice Foundation
OBJECTIVES: The coronavirus disease 2019 (COVID-19) has caused a crisis worldwide. Amounts of efforts have been made to prevent and control COVID-19's transmission, from early screenings to vaccinations and treatments. Recently, due to the spring up ...

Impact of Artificial Intelligence Assistance on Chest CT Interpretation Times: A Prospective Randomized Study.

AJR. American journal of roentgenology
Deep learning-based convolutional neural networks have enabled major advances in development of artificial intelligence (AI) software applications. Modern AI applications offer comprehensive multiorgan evaluation. The purpose of this article was to...

Radiomics and artificial intelligence in prostate cancer: new tools for molecular hybrid imaging and theragnostics.

European radiology experimental
In prostate cancer (PCa), the use of new radiopharmaceuticals has improved the accuracy of diagnosis and staging, refined surveillance strategies, and introduced specific and personalized radioreceptor therapies. Nuclear medicine, therefore, holds gr...

Deep Learning to Optimize Candidate Selection for Lung Cancer CT Screening: Advancing the 2021 USPSTF Recommendations.

Radiology
Background A deep learning (DL) model to identify lung cancer screening candidates based on their chest radiographs requires external validation with a recent real-world non-U.S. sample. Purpose To validate the DL model and identify added benefits to...