AIMC Topic: Aged

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Rapid whole-heart CMR with single volume super-resolution.

Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance
BACKGROUND: Three-dimensional, whole heart, balanced steady state free precession (WH-bSSFP) sequences provide delineation of intra-cardiac and vascular anatomy. However, they have long acquisition times. Here, we propose significant speed-ups using ...

Data mining for sex estimation based on cranial measurements.

Forensic science international
The aim of the present study is to develop effective and understandable classification models for sex estimation and to identify the most dimorphic linear measurements in adult crania by means of data mining techniques. Furthermore, machine learning ...

Personalized machine learning approach to predict candidemia in medical wards.

Infection
PURPOSE: Candidemia is a highly lethal infection; several scores have been developed to assist the diagnosis process and recently different models have been proposed. Aim of this work was to assess predictive performance of a Random Forest (RF) algor...

Robust Estimation of Breast Cancer Incidence Risk in Presence of Incomplete or Inaccurate Information.

Asian Pacific journal of cancer prevention : APJCP
PURPOSE: To evaluate the robustness of multiple machine learning classifiers for breast cancer risk estimation in the presence of incomplete or inaccurate information.

Prediction of the development of acute kidney injury following cardiac surgery by machine learning.

Critical care (London, England)
BACKGROUND: Cardiac surgery-associated acute kidney injury (CSA-AKI) is a major complication that results in increased morbidity and mortality after cardiac surgery. Most established prediction models are limited to the analysis of nonlinear relation...

Machine learning approach to predict postoperative opioid requirements in ambulatory surgery patients.

PloS one
Opioids play a critical role in acute postoperative pain management. Our objective was to develop machine learning models to predict postoperative opioid requirements in patients undergoing ambulatory surgery. To develop the models, we used a periope...

Automated Assessment of COVID-19 Reporting and Data System and Chest CT Severity Scores in Patients Suspected of Having COVID-19 Using Artificial Intelligence.

Radiology
Background The coronavirus disease 2019 (COVID-19) pandemic has spread across the globe with alarming speed, morbidity, and mortality. Immediate triage of patients with chest infections suspected to be caused by COVID-19 using chest CT may be of assi...

AD risk score for the early phases of disease based on unsupervised machine learning.

Alzheimer's & dementia : the journal of the Alzheimer's Association
INTRODUCTION: Identifying cognitively normal individuals at high risk for progression to symptomatic Alzheimer's disease (AD) is critical for early intervention.

Changes in technology acceptance among older people with dementia: the role of social robot engagement.

International journal of medical informatics
OBJECTIVE: Emerging technologies such as social robots have shown to be effective in reducing loneliness and agitation for older people with dementia. However, the acceptance of technology (specifically social robots) was found to be low for older pe...