Research background

Bian Que's Tale (扁鵲, BC 407-301)

Bian Que was an ancient Chinese physician, often considered one of the earliest known practitioners of medicine in China, renowned for his expertise in pulse diagnosis and herbal medicine.
Bian Que, the youngest of three doctor brothers, considered his eldest brother the best, followed by the middle brother, and himself the least skilled.
The emperor asked why Bian Que's name was the most well-known if his brothers were so skilled.
Bian Que explained that his eldest brother could detect and treat serious illnesses early, before patients felt any pain, so patients were unaware of his intervention.
His second brother treated illnesses at an early stage, preventing severe conditions, but people did not realize the severity of the averted illnesses.
As a result, Bian Que's brothers were seen as treating only minor ailments and their names remained local, while Bian Que's reputation spread due to treating visibly severe illnesses.

Image from Wikipedia.

Challenges in Biomedical Research

Not enough focus on health, prevention, and early detection of disease.
Transitions between health and disease are poorly understood and only superficially characterized.
Lack of significant information over dimension of time.
Hypothesis-driven studies focus on specific mechanisms.
Missing the ability to measure the interactions of biology, sociology, environment, and decision-making that could enable optimization of individualized and population health.

precision health

Precision health is a medical approach that tailors healthcare interventions and strategies to individual patients based on their unique genetic, biomarker, phenotypic, or psychosocial characteristics. This approach aims to optimize medical care by predicting which treatments will be effective for specific patients, thus enhancing treatment efficacy and reducing side effects. Precision health extends beyond individualized treatment plans to encompass preventative measures, ensuring that interventions are proactive rather than reactive. It leverages advanced technologies like genomics, data analytics, and artificial intelligence to understand the complex interplay of genetic and environmental factors in disease. The ultimate goal is to improve health outcomes and promote wellness by delivering the right treatment to the right patient at the right time.

Gambhir et al. ,Toward achieving precision health. Sci Transl Med 10, eaao3612 (2018).

wearables

Emerging technologies – but user adoption/compliance may be barriers.

Gambhir et al. ,Toward achieving precision health. Sci Transl Med 10, eaao3612 (2018).

smart home

Permit high-frequency monitoring without requiring a change in user behavior.

Gambhir et al. ,Toward achieving precision health. Sci Transl Med 10, eaao3612 (2018).

digital biomarkers

Physiological, biochemical, and behavioral data collected by smart devices – quantitative.
Can be collectively analyzed with predictive modeling and artificial intelligence for health pattern recognition and enable actionable response determination.
e.g., COVID-19 screening with smart watch data.
Smart Watches, Phones, Homes – not in the bathroom.
“Digitization” of events, “Digitalization” of disease management ”Digital Transformation” of healthcare.

Project Baseline

Verily - Stanford Medicine - Duke Medicine.
Project Baseline is a quest to map human health.
Primary goals:
1. Better understand the transition from health to disease.
2. Identify early precursors of disease.
3. Develop new tools and technologies for accessing and analyzing health data.
Collect a variety of health information using an individual’s unique history, genetics, and lifestyle.
Organize information into a digital platform – “Google Maps for Health”.

Smart healthcare toilet

Park et al. Nat Biomed Eng, 4, 624-635 (2020).
Park* et al. Nat Rev Gastroenterol Hepatol, 18, 521–522 (2021).
Park* et al. npj Digit Med, 5, 39 (2022).
Park* et al. Sci Trans Med, abk3489 (2023).
Park S.-m.* Nat Rev Gastroenterol Hepatol, 21, 217 (2024).
United States Patent Applications: US11604177B1

*Corresponding author

Past research statement

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