Job description

Dance4Healing, a Singularity University/Stanford startup, is seeking a Video Technologist for an upcoming National Institute on Minority Health and Health Disparities (NIMHD) study. Apply at https://bit.ly/D4H_TechTalent if interested.

Dance4Healing (D4H) is an award-winning social venture founded by a UX and behavior expert months after recovering from Stage IV cancer. D4H’s Stanford Cancer Supportive Care Program achieved a Net Promoter Score (NPS) of 91 from 90+ patients; most reported significant improvement in anxiety, depression, pain, and energy levels.

Guided by The NIMHD Research Framework, this research will study the effects of intersectional identities on racial/ethnic equity, reduce Artificial Intelligence (AI) bias, and develop a culturally sensitive novel habit-building algorithm for minority Diabetes Mellitus (DM) patients using Creative Arts Therapy (CAT: Music, Dance, Arts) for remote activity engagement systems with multilevel data tracking and effective behavior prompts. We will partner with Stanford, Institute on Aging, Koelsch Communities, Generation United, and Heritage On The Marina to develop a groundbreaking smart platform integrating biosensors and a Telehealth Live Video Platform (TLVP). This project aims to gather insights into different domains (Biological, Behavioral, Physical/Built Environment, Sociocultural Environment, Healthcare System) and levels (Individual, Interpersonal, Community, Societal) that influence healthy habits, then analyze the data to adapt D4H to improve patients’ mobility and social connections. D4H’s proprietary personalization will tailor to users’ needs/desires and pair them with compatible buddies to build lasting habits with recorded and live video classes (think YouTube + Zoom + eHarmony for health buddies).

You will work with a multidisciplinary team of experts in health disparity, diabetes, cardiovascular health, biotracking, behavioral sciences, dance therapy, and data/AI science. Research experience is a bonus but not required.

AI scientist Role:

• Develop a unique multi-data collection protocol (fitness watch, Omran scale, platform, and clinical survey).

• Build culturally sensitive AI tailored to preferences, mobility/accessibility needs, and potential language barriers.

• Ensure accurate data collection and analysis.

• Develop multimedia solutions, and build the biodata collection methodology.

• Build a HIPAA-compliant data server, and integrate bio-sensor data into the virtual platform.

• Ensure privacy and security for participants.

Why this study: 34.2 M Americans with DM cost $327 B in 2018. 68% of them will die from cardiovascular disease. CDC reported that DM disproportionately affects minorities. Partnering with Stanford professors Dr. Palaniappan and Dr. Haddad, who have pioneered research on health disparities and exercise/dance intervention for DM patients, this innovation will expand the research field and have a broader impact on minority health. Currently, there is a lack of data on effective lifestyle recommendations for normal-weight diabetics (NWD), accounting for 1 in 5 Type II DM patients. NWD is especially prevalent in Asian populations and the elderly, facing higher mortality rates than obese diabetics. Research shows dance improves DM and reduces cardiovascular deaths by 46%. These interventions, however, are only available in person. There are many exercise programs and live video tools, but they rarely cater to an individual’s mobility and accessibility needs. Hence, there is an unmet need for an easy-to-adopt telehealth platform enticing patients to dance from home.

AI Bias: Integrating AI into clinical practice requires addressing biases. Three types of bias can be identified in healthcare: data-driven, algorithmic, and human. AI algorithms that propagate deeply-rooted societal bias can have catastrophic impacts. Consequently, some patient groups, such as ethnic and gender minorities underrepresented in existing datasets, can be misdiagnosed, further amplifying inequalities. Every step of the algorithm development process can be influenced by bias. It begins when designing the study and collecting data, continues with data entry, cleaning, and algorithm design, and ends with implementing the models and disseminating the results.

Impact and Next Step: This study will establish clear metrics of health equity success; outcomes will be publicized (papers/conferences) to incentivize action and influence policymakers. It will lay the groundwork for a multicenter trial with American Heart Association to integrate more biosensors, voice user interfaces, and culture-sensitive AI to further increase adoption and engagement and reduce health disparities.

Job Type: Contract

Pay: Up to $149,847.93 per year

Benefits:

• Flexible schedule

COVID-19 considerations:
We are committed to building a fun and supportive working environment by hosting three co-working sessions weekly to offer teambuilding, expert education, mentorship, advice, feedback, and accountability.

Experience:

• AI: 3 years (Preferred)
• Machine Learning: 5 years (Preferred)

Work Location: Remote

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