AIMC Topic: Machine Learning

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Deep Learning and Mathematical Models in Dermatology.

Actas dermo-sifiliograficas Jan 3, 2020
Machine Learning Deep Learning Models, Theoretical Skin Diseases Dermatology Humans
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Artificial Intelligence in Cancer Staging: Limitless Potential or Passing Fad?

Annals of surgical oncology Jan 3, 2020
Treatment Outcome Neoplasm Staging Bile Duct Neoplasms Cholangiocarcinoma Humans Prognosis Machine Learning Clinical Decision-Making Surgeons
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Harnessing big 'omics' data and AI for drug discovery in hepatocellular carcinoma.

Nature reviews. Gastroenterology & hepatology Jan 3, 2020
Hepatocellular carcinoma (HCC) is the most common form of primary adult liver cancer. After nearly a decade with sorafenib as the only approved treatment, multiple new agents have demonstrated efficacy in clinical trials, including the targeted thera...
Carcinoma, Hepatocellular Genomics Disease Models, Animal Translational Research, Biomedical Antineoplastic Agents Cell Line, Tumor Liver Neoplasms Molecular Targeted Therapy Humans Artificial Intelligence Machine Learning Animals Drug Discovery Biomarkers Precision Medicine
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Distributed learning on 20 000+ lung cancer patients - The Personal Health Train.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology Jan 3, 2020
BACKGROUND AND PURPOSE: Access to healthcare data is indispensable for scientific progress and innovation. Sharing healthcare data is time-consuming and notoriously difficult due to privacy and regulatory concerns. The Personal Health Train (PHT) pro...
China Lung Neoplasms Privacy Humans Machine Learning Algorithms
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Graph Convolutional Neural Networks as "General-Purpose" Property Predictors: The Universality and Limits of Applicability.

Journal of chemical information and modeling Jan 3, 2020
Nowadays the development of new functional materials/chemical compounds using machine learning (ML) techniques is a hot topic and includes several crucial steps, one of which is the choice of chemical structure representation. The classical approach ...
Structure-Activity Relationship Density Functional Theory Models, Molecular Crystallization Neural Networks, Computer Machine Learning Algorithms
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Assessment of a Machine Learning Model Applied to Harmonized Electronic Health Record Data for the Prediction of Incident Atrial Fibrillation.

JAMA network open Jan 3, 2020
IMPORTANCE: Atrial fibrillation (AF) is the most common sustained cardiac arrhythmia, and its early detection could lead to significant improvements in outcomes through the appropriate prescription of anticoagulation medication. Although a variety of...
Adult Male Risk Assessment Middle Aged Atrial Fibrillation Humans Female Logistic Models Aged Machine Learning Young Adult Electronic Health Records
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Comparison of Machine Learning Methods With Traditional Models for Use of Administrative Claims With Electronic Medical Records to Predict Heart Failure Outcomes.

JAMA network open Jan 3, 2020
IMPORTANCE: Accurate risk stratification of patients with heart failure (HF) is critical to deploy targeted interventions aimed at improving patients' quality of life and outcomes.
Hospitalization United States Aged Machine Learning Comorbidity Humans Aged, 80 and over Electronic Health Records Cohort Studies Male Medicare Female Logistic Models Heart Failure Outcome Assessment, Health Care
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Use of Machine Learning for Predicting Escitalopram Treatment Outcome From Electroencephalography Recordings in Adult Patients With Depression.

JAMA network open Jan 3, 2020
IMPORTANCE: Social and economic costs of depression are exacerbated by prolonged periods spent identifying treatments that would be effective for a particular patient. Thus, a tool that reliably predicts an individual patient's response to treatment ...
Biomarkers Prognosis Female Reproducibility of Results Humans Machine Learning Support Vector Machine Predictive Value of Tests Electroencephalography Citalopram Antidepressive Agents, Second-Generation Middle Aged Depressive Disorder, Major Canada Treatment Outcome Adult Sensitivity and Specificity Male
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The Detection of Opioid Misuse and Heroin Use From Paramedic Response Documentation: Machine Learning for Improved Surveillance.

Journal of medical Internet research Jan 3, 2020
BACKGROUND: Timely, precise, and localized surveillance of nonfatal events is needed to improve response and prevention of opioid-related problems in an evolving opioid crisis in the United States. Records of naloxone administration found in prehospi...
Emergency Medical Services Analgesics, Opioid Drug Overdose Heroin Female Allied Health Personnel Male Humans Machine Learning
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A practical model for the identification of congenital cataracts using machine learning.

EBioMedicine Jan 3, 2020
BACKGROUND: Approximately 1 in 33 newborns is affected by congenital anomalies worldwide. We aimed to develop a practical model for identifying infants with a high risk of congenital cataracts (CCs), which is the leading cause of avoidable childhood ...
Humans Machine Learning Risk Factors ROC Curve Algorithms Male Models, Biological Case-Control Studies Area Under Curve Female Inheritance Patterns Child, Preschool Cataract Reproducibility of Results
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