Patients with cancer often exhibit multiple co-occurring symptoms which can impact the type of treatment received, recovery, and long-term health. We aim to simultaneously predict the risk of three symptoms: severe pain, moderate-severe depression, a...
Journal of nursing scholarship : an official publication of Sigma Theta Tau International Honor Society of Nursing
33348455
PURPOSE: The main objective of this study was to utilize an artificial neural network in an exploratory fashion to predict self-management behaviors based on reported symptoms in a sample of stable patients with chronic obstructive pulmonary disease ...
Early prediction of patient mortality risks during a pandemic can decrease mortality by assuring efficient resource allocation and treatment planning. This study aimed to develop and compare prognosis prediction machine learning models based on invas...
BACKGROUND: Patients with mental health disorders often have difficulty perceiving associations between multiple symptoms, such as inter-relations between somatic and psychological symptoms. This difficulty may be particularly challenging in patients...
Receiving timely and appropriate treatment is crucial for better health outcomes, and research on the contribution of specific variables is essential. In the mental health domain, an important research variable is the date of psychosis symptom onset,...
OBJECTIVE: Identifying symptoms and characteristics highly specific to coronavirus disease 2019 (COVID-19) would improve the clinical and public health response to this pandemic challenge. Here, we describe a high-throughput approach - Concept-Wide A...
Journal of the American Medical Informatics Association : JAMIA
33674830
The COVID-19 pandemic swept across the world rapidly, infecting millions of people. An efficient tool that can accurately recognize important clinical concepts of COVID-19 from free text in electronic health records (EHRs) will be valuable to acceler...
European review for medical and pharmacological sciences
34533806
OBJECTIVE: This paper aims to develop four prediction models for recovered and unrecovered cases using descriptive data of patients and symptoms of CoVID-19 patients. The developed prediction models aim to extract the important variables in predictin...
Decision making on the treatment of vestibular schwannoma (VS) is mainly based on the symptoms, tumor size, patient's preference, and experience of the medical team. Here we provide objective tools to support the decision process by answering two que...