AIMC Topic: Age Factors

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Deep learning assessment of breast terminal duct lobular unit involution: Towards automated prediction of breast cancer risk.

PloS one Apr 15, 2020
Terminal duct lobular unit (TDLU) involution is the regression of milk-producing structures in the breast. Women with less TDLU involution are more likely to develop breast cancer. A major bottleneck in studying TDLU involution in large cohort studie...
Image Processing, Computer-Assisted Breast Neoplasms Humans Age Factors Female Biopsy Reproducibility of Results Middle Aged Breast Risk Factors Risk Assessment Adult Deep Learning Cohort Studies
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Identifying predictive features of autism spectrum disorders in a clinical sample of adolescents and adults using machine learning.

Scientific reports Mar 18, 2020
Diagnosing autism spectrum disorders (ASD) is a complicated, time-consuming process which is particularly challenging in older individuals. One of the most widely used behavioral diagnostic tools is the Autism Diagnostic Observation Schedule (ADOS). ...
Age Factors Diagnosis, Differential Symptom Assessment Psychological Tests Sensitivity and Specificity Male Psychometrics Adolescent Autism Spectrum Disorder Support Vector Machine Female Reproducibility of Results Humans Young Adult Machine Learning Adult Algorithms
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Artificial neural network-based models used for predicting 28- and 90-day mortality of patients with hepatitis B-associated acute-on-chronic liver failure.

BMC gastroenterology Mar 13, 2020
BACKGROUND: This study aimed to develop prognostic models for predicting 28- and 90-day mortality rates of hepatitis B virus (HBV)-associated acute-on-chronic liver failure (HBV-ACLF) through artificial neural network (ANN) systems.
Hepatitis B e Antigens Alkaline Phosphatase Sodium gamma-Glutamyltransferase Bilirubin Adult Male Hepatitis B Age Factors Acute-On-Chronic Liver Failure Prothrombin Time Hepatic Encephalopathy Humans Neural Networks, Computer Prognosis Retrospective Studies Female Risk Factors
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Artificial neural networks allow response prediction in squamous cell carcinoma of the scalp treated with radiotherapy.

Journal of the European Academy of Dermatology and Venereology : JEADV Mar 4, 2020
BACKGROUND: Epithelial neoplasms of the scalp account for approximately 2% of all skin cancers and for about 10-20% of the tumours affecting the head and neck area. Radiotherapy is suggested for localized cutaneous squamous cell carcinomas (cSCC) wit...
Aged Phenotype Aged, 80 and over Humans Male Neural Networks, Computer Head and Neck Neoplasms Retrospective Studies Neoplasm Recurrence, Local Middle Aged Forecasting Age Factors Female Radiotherapy Dosage Treatment Outcome Neoplasm Staging Scalp Skin Neoplasms Carcinoma, Squamous Cell
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Factors that affect younger and older adults' causal attributions of robot behaviour.

Ergonomics Mar 4, 2020
Stereotypes are cognitive shortcuts that facilitate efficient social judgments about others. Just as causal attributions affect perceptions of people, they may similarly affect perceptions of technology, particularly anthropomorphic technology such a...
Young Adult Adult Male Adolescent Age Factors Robotics Humans Female Aged Stereotyping Social Perception
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Prediction of perioperative transfusions using an artificial neural network.

PloS one Feb 24, 2020
BACKGROUND: Accurate prediction of operative transfusions is essential for resource allocation and identifying patients at risk of postoperative adverse events. This research examines the efficacy of using artificial neural networks (ANNs) to predict...
Humans Perioperative Care Neural Networks, Computer Machine Learning Sensitivity and Specificity Blood Transfusion Databases, Factual Male Postoperative Hemorrhage Computer Simulation Age Factors Sex Factors Prognosis Female Risk Factors
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Measuring the impact of age, gender and dementia on communication-robot interventions in residential care homes.

Geriatrics & gerontology international Feb 19, 2020
AIM: The primary aim of this study was to examine the impact of age, gender and the stage of dementia on the results of an assistive technology intervention that make use of communication robots (com-robots). The intervention was designed to improve ...
Dementia Cohort Studies Age Factors Robotics Japan Sex Factors Nursing Homes Self-Help Devices Homes for the Aged Aged, 80 and over Communication Male Quality of Life Disease Progression Humans Delivery of Health Care Female Aged
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Preoperative prediction of parametrial invasion in early-stage cervical cancer with MRI-based radiomics nomogram.

European radiology Feb 17, 2020
PURPOSE: To develop and identify a MRI-based radiomics nomogram for the preoperative prediction of parametrial invasion (PMI) in patients with early-stage cervical cancer (ECC).
Humans Age Factors Adult Magnetic Resonance Imaging Algorithms Neoplasm Invasiveness Hysterectomy Uterine Cervical Neoplasms Retrospective Studies Middle Aged Neoplasm Grading Informatics Female Nomograms Diffusion Magnetic Resonance Imaging Reproducibility of Results Peritoneum Support Vector Machine Aged
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Identifying treatment effects of an informal caregiver education intervention to increase days in the community and decrease caregiver distress: a machine-learning secondary analysis of subgroup effects in the HI-FIVES randomized clinical trial.

Trials Feb 14, 2020
BACKGROUND: Informal caregivers report substantial burden and depressive symptoms which predict higher rates of patient institutionalization. While caregiver education interventions may reduce caregiver distress and decrease the use of long-term inst...
Male Middle Aged Quality of Life Depression Stress, Psychological Humans Machine Learning Female Aged Aged, 80 and over Data Interpretation, Statistical Veterans Family Caregivers Cognitive Dysfunction Institutionalization Treatment Outcome Long-Term Care Follow-Up Studies Age Factors Randomized Controlled Trials as Topic
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Mixed-integer optimization approach to learning association rules for unplanned ICU transfer.

Artificial intelligence in medicine Jan 30, 2020
After admission to emergency department (ED), patients with critical illnesses are transferred to intensive care unit (ICU) due to unexpected clinical deterioration occurrence. Identifying such unplanned ICU transfers is urgently needed for medical p...
Patient Transfer Hospitals, Teaching Logistic Models Humans Models, Theoretical Machine Learning Age Factors Critical Illness Emergency Service, Hospital Intensive Care Units Quality Improvement Severity of Illness Index Time Factors
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