A deep learning algorithm to prevent burnout risk in Family Caregivers of patients undergoing dialysis treatment.
Vania CostaMartina MessinaMario BottoneRaffaele SperandeoAnna EspositoNelson Mauro MaldonatoValeria CioffiGiuseppina di RonzaDaniela IennacoPasquale DolceEnrico MorettoPublished in: CogInfoCom (2018)
Keyphrases
- acute coronary syndrome
- learning algorithm
- disease progression
- patient data
- chronic disease
- high risk
- medical data
- intensive care unit
- vital signs
- patient outcomes
- medical practitioners
- medical practice
- medical treatment
- health care
- medical care
- medical staff
- risk factors
- machine learning algorithms
- clinical data
- cancer patients
- active learning
- cross sectional
- clinical trials
- therapy planning
- prostate cancer
- breast cancer
- medical doctors
- electronic medical record
- clinical studies
- real patient data
- liver disease
- mathematical modeling
- risk assessment
- blood vessels
- ischemic stroke
- training data
- cancer treatment
- supervised learning
- reinforcement learning
- treatment plan
- breast cancer patients
- machine learning
- clinical information
- clinical diagnosis
- medical records
- back propagation
- cardiovascular disease
- heart rate
- magnetic resonance images
- risk management
- pregnant women
- acute myeloid
- clinically relevant
- intensive care
- assistive technology
- deep brain stimulation
- intraoperative
- acute myocardial infarction