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Persuasive robots should avoid authority: The effects of formal and real authority on persuasion in human-robot interaction.

Science robotics
Social robots must take on many roles when interacting with people in everyday settings, some of which may be authoritative, such as a nurse, teacher, or guard. It is important to investigate whether and how authoritative robots can influence people ...

Implementation of artificial intelligence algorithms for melanoma screening in a primary care setting.

PloS one
Skin cancer is currently the most common type of cancer among Caucasians. The increase in life expectancy, along with new diagnostic tools and treatments for skin cancer, has resulted in unprecedented changes in patient care and has generated a great...

A Nomogram for the Prediction of Intermediate Significant Renal Function Loss After Robot-assisted Partial Nephrectomy for Localized Renal Tumors: A Prospective Multicenter Observational Study (RECORd2 Project).

European urology focus
BACKGROUND: Robot-assisted partial nephrectomy (RAPN) is increasingly adopted for the treatment of localized renal tumors; however, rates and predictors of significant renal function (RF) loss after RAPN are still poorly investigated, especially at a...

Deep Learning for Adjacent Segment Disease at Preoperative MRI for Cervical Radiculopathy.

Radiology
Background Patients who undergo surgery for cervical radiculopathy are at risk for developing adjacent segment disease (ASD). Identifying patients who will develop ASD remains challenging for clinicians. Purpose To develop and validate a deep learnin...

Deep learning methods for automatic segmentation of lower leg muscles and bones from MRI scans of children with and without cerebral palsy.

NMR in biomedicine
Cerebral palsy is a neurological condition that is known to affect muscle growth. Detailed investigations of muscle growth require segmentation of muscles from MRI scans, which is typically done manually. In this study, we evaluated the performance o...

Deep learning-based prediction of early cerebrovascular events after transcatheter aortic valve replacement.

Scientific reports
Cerebrovascular events (CVE) are among the most feared complications of transcatheter aortic valve replacement (TAVR). CVE appear difficult to predict due to their multifactorial origin incompletely explained by clinical predictors. We aimed to build...

Non-invasive diagnostic tool for Parkinson's disease by sebum RNA profile with machine learning.

Scientific reports
Parkinson's disease (PD) is a progressive neurodegenerative disease presenting with motor and non-motor symptoms, including skin disorders (seborrheic dermatitis, bullous pemphigoid, and rosacea), skin pathological changes (decreased nerve endings an...

A Machine Learning Model for Evaluating Imported Disease Screening Strategies in Immigrant Populations.

The American journal of tropical medicine and hygiene
Given the high prevalence of imported diseases in immigrant populations, it has postulated the need to establish screening programs that allow their early diagnosis and treatment. We present a mathematical model based on machine learning methodologie...

Identification of clinical trait-related small RNA biomarkers with weighted gene co-expression network analysis for personalized medicine in endocervical adenocarcinoma.

Aging
Endocervical adenocarcinoma (EAC) is an aggressive type of endocervical cancer. At present, molecular research on EAC mainly focuses on the genome and mRNA transcriptome, the investigation of small RNAs in EAC has not been fully described. Here, we s...

Estimation of Baseline Serum Creatinine with Machine Learning.

American journal of nephrology
INTRODUCTION: Comparing current to baseline serum creatinine is important in detecting acute kidney injury. In this study, we report a regression-based machine learning model to predict baseline serum creatinine.