Toward achieving precision health

Abstract

Health care systems primarily focus on patients after they present with disease, not before. The emerging field of precision health encourages disease prevention and earlier detection by monitoring health and disease based on an individual’s risk. Active participation in health care can be encouraged with continuous health-monitoring devices, providing a higher-resolution picture of human health and disease. However, the development of monitoring technologies must prioritize the collection of actionable data and long-term user engagement.

The Jiangnan diet, a healthy diet pattern for Chinese

“…Other confounding factors including age, gender, ethnic and genetic differences, physical activity, smoking and drinking habits, basal metabolic rate, stress and mental status, and even gut microbes also have interaction with diet and should be well controlled and well recorded. 52 It will be a breakthrough to resolve these difficulties and provide some evidence about which diet produces more benefits on health. It could be concluded that both the traditional Mediterranean diet and the traditional Jiangnan diet are close to the Healthy Plate Recommendation by Harvard Nutrition.…”

Cross-Modal Health State Estimation

“…Health state estimation and tracking has been an important field in medical literature and computer science. There has been a strong call by the medical science community to use continuous multimodal data for tracking individual health [29,30,36,43,48]. Most modern metrics that are used to understand patient health were derived from longitudinal studies of large cohorts to see what led to morbidity and mortality.…”

Using person‐specific neural networks to characterize heterogeneity in eating disorders: Illustrative links between emotional eating and ovarian hormones

“…The eating disorder group is often more heterogeneous than the control group in clinical research (e.g., in neural signals; Bohon & Stice, 2011;Marsh et al, 2009), and a focus on mean-level differences might produce biased estimates because the average is not representative (Molenaar, 2004). Focusing on the individual is also consistent with the rising prominence of precision healthcare (Davidson & Cheung, 2017;Gambhir et al, 2018), and has demonstrated importance in clinically-relevant phenomena. In personality research, person-specific analyses have shown that the common five-factor model explaining variation between people only applies to 14% of individuals (Molenaar & Campbell, 2009).…”

“…Second, "average" people do not walk into clinics; individuals do. Treatments developed from homogenous sample averages may contribute to poor responses from heterogeneous individuals, highlighting the need for precision healthcare (Davidson & Cheung, 2017;Gambhir, Ge, Vermesh, & Spitler, 2018).…”