The Potential of Evidence-Based Clinical Intake Tools to Discover or Ground Prevalence of Symptoms Using Real-Life Digital Health Encounters: Retrospective Cohort Study.

Background: Evidence-based clinical intake tools (EBCITs) are structured assessment tools used to gather information about patients and help health care providers make informed decisions. The growing demand for personalized medicine, along with the big data revolution, has rendered EBCITs a promising solution. EBCITs have the potential to provide comprehensive and individualized assessments of symptoms, enabling accurate diagnosis, while contributing to the grounding of medical care.

Validation of a novel Artificial Pharmacology Intelligence (API) system for the management of patients with polypharmacy.

Objective: Medication management of patients with polypharmacy is highly complex. We aimed to validate a novel Artificial Pharmacology Intelligence (API) algorithm to optimize the medication review process in a comprehensive, personalized, and scalable way.

Materials And Methods: The study was conducted on anonymized retrospective electronic health records (EHR) of 49 patients.

Digitally enabled asynchronous remote medical management of anxiety and depression: A cohort study.

Objective: To evaluate the clinical outcomes of a remote mental health program for managing anxiety and depression, primarily using asynchronous digital communication.

Methods: This retrospective cohort study examined U.S.

The Association of Macronutrient Consumption and BMI to Exhaled Carbon Dioxide in Lumen Users: Retrospective Real-World Study.

Background: Metabolic flexibility is the ability of the body to rapidly switch between fuel sources based on their accessibility and metabolic requirements. High metabolic flexibility is associated with improved health outcomes and a reduced risk of several metabolic disorders. Metabolic flexibility can be improved through lifestyle changes, such as increasing physical activity and eating a balanced macronutrient diet.

Characteristics and Symptoms of App Users Seeking COVID-19-Related Digital Health Information and Remote Services: Retrospective Cohort Study.

Background: Patient-facing digital health tools have been promoted to help patients manage concerns related to COVID-19 and to enable remote care and self-care during the COVID-19 pandemic. It has also been suggested that these tools can help further our understanding of the clinical characteristics of this new disease. However, there is limited information on the characteristics and use patterns of these tools in practice.

"A patient like me" - An algorithm-based program to inform patients on the likely conditions people with symptoms like theirs have.

To date, consumer health tools available over the web suffer from serious limitations that lead to low quality health- related information. While health data in our world are abundant, access to it is limited because of liability and privacy constraints.The objective of the present study was to develop and evaluate an algorithm-based tool which aims at providing the public with reliable, data-driven information based and personalized information regarding their symptoms, to help them and their physicians to make better informed decisions, based on statistics describing "people like you", who have experienced similar symptoms.

Ocular complications in children after hematopoietic stem cell transplantation without total body irradiation.

Purpose: The purpose of the study was to evaluate whether hematopoietic stem cell transplantation (HSCT) without conditioning Total Body Irradiation (TBI) had lower or milder ocular complication rates in the pediatric population.

Methods: This study included all children who underwent HSCT without conditioning TBI at the Chaim Sheba Medical Center between the years 2001 and 2008. All children had an ophthalmic evaluation prior to and every four months after HSCT.