Search Articles

View query in Help articles search
e.g. mhealth

Search Results (1 to 3 of 3 Results)

Download search results: CSV END BibTex RIS

The Alzheimer’s Knowledge Base: A Knowledge Graph for Alzheimer Disease Research

The Alzheimer’s Knowledge Base: A Knowledge Graph for Alzheimer Disease Research

We repeated these steps several times, making revisions on previous iterations until several domain experts agreed that the semantic contents of the ontology were consistent with current AD knowledge and systems biology processes involved in AD etiology.

Joseph D Romano, Van Truong, Rachit Kumar, Mythreye Venkatesan, Britney E Graham, Yun Hao, Nick Matsumoto, Xi Li, Zhiping Wang, Marylyn D Ritchie, Li Shen, Jason H Moore

J Med Internet Res 2024;26:e46777

Download Citation: END BibTex RIS

Download PDF Download XML
Article has an altmetric score of 14

Predicting Overweight and Obesity Status Among Malaysian Working Adults With Machine Learning or Logistic Regression: Retrospective Comparison Study

Predicting Overweight and Obesity Status Among Malaysian Working Adults With Machine Learning or Logistic Regression: Retrospective Comparison Study

However, given the complexity of the etiology of obesity, regression modeling may not be adept at disentangling nonlinear and interdependent relationships among factors for obesity prediction. Machine learning (ML) is an advanced data analytical method that uses fine-tuned algorithms to characterize and predict outcomes by learning from data without being explicitly programmed to do so.

Jyh Eiin Wong, Miwa Yamaguchi, Nobuo Nishi, Michihiro Araki, Lei Hum Wee

JMIR Form Res 2022;6(12):e40404

Download Citation: END BibTex RIS

Download PDF Download XML
Article has an altmetric score of 2

Determining the Cause of Death Among Children Hospitalized With Respiratory Illness in Kenya: Protocol for Pediatric Respiratory Etiology Surveillance Study (PRESS)

Determining the Cause of Death Among Children Hospitalized With Respiratory Illness in Kenya: Protocol for Pediatric Respiratory Etiology Surveillance Study (PRESS)

This study describes the methodology for the Pediatric Respiratory Etiology Surveillance Study (PRESS), which was conducted prospectively to investigate the cause of death and associated microbial etiologies among children (age 1-59 months) hospitalized for respiratory illness in Kenya.

Henry N S Njuguna, Sherif R Zaki, Drucilla J Roberts, Corinne L Fligner, M. Kelly Keating, Emily Rogena, Edwin Walong, Andrew K Gachii, Elizabeth Maleche-Obimbo, Grace Irimu, John Mathaiya, Noelle Orata, Rosemarie Lopokoiyit, Jackson Maina, Gideon O Emukule, Clayton O Onyango, Stella Gikunju, Collins Owuor, Peter Kinuthia, Milka Bunei, Barry Fields, Marc-Alain Widdowson, Joshua A Mott, Sandra S Chaves

JMIR Res Protoc 2019;8(1):e10854

Download Citation: END BibTex RIS

Download PDF Download XML
Article has an altmetric score of 12