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Tag: machine learning
06/20/2023

AI Plus Mobile App May Help With Smoking Cessation

Article Excerpt: A new artificial intelligence (AI)-powered mobile app can help individuals quit smoking, according to the results of a recent study published in Nicotine & Tobacco Research. The app uses machine learning to collect information on the location, timing, and triggers of past smoking events to curate messages that assist smokers in managing their urges. Prior to this app, there had been no other ways to provide support to help smokers manage social situations and urges after quitting, Felix Naughton, PhD, MSc, a primary researcher and professor of health psychology at the University of East Anglia School of Health Sciences in England, said in a statement.

Full Article: https://tinyurl.com/yc56jtx9

Article Source: Pharmacy Times

Posted in: Emerging Technologies // Tagged: ; ; ; ; ; ;
06/09/2023

DHMC Campus to Host AI Initiative

Article Excerpt: With $2 million, the Geisel School of Medicine and the Dartmouth Cancer Center are launching a new Center for Precision Health and Artificial Intelligence on the Dartmouth Hitchcock Medical Center campus in Lebanon. The new center, which will be based in the Williamson Translational Research Building on DHMC’s campus, aims to bring together related research and clinical efforts across Dartmouth to use information about patients’ biology, such as genetics, medical history, lifestyle and environment to create personalized treatment plans and disease-prevention strategies in order to improve people’s health. “It is a very active domain of research,” Saeed Hassanpour, a Dartmouth associate professor of biomedical data science, epidemiology and computer science and the center’s inaugural director, said in a phone interview. “There’s a lot of promise.”

Full Article: https://tinyurl.com/4zvp4rkb

Article Source: Valley News

Posted in: Methodologies & Analytics // Tagged: ; ; ; ; ; ; ;
06/07/2023

Dartmouth Launches Center for Artificial Intelligence, Precision Medicine

Article Excerpt: Dartmouth launched its Center for Precision Health and Artificial Intelligence (CPHAI) this week, which is set to advance interdisciplinary research into how artificial intelligence (AI) and biomedical data can be used to improve precision medicine and health outcomes. CPHAI’s launch is supported by $2 million in initial funding from Dartmouth’s Geisel School of Medicine and the Dartmouth Cancer Center. The center’s research aims to improve public health and healthcare delivery while maintaining rigorous ethical standards for health AI, according to CPHAI’s website.

Full Article: https://tinyurl.com/2p983hnm

Article Source: Precision Medicine News

Posted in: Methodologies & Analytics // Tagged: ; ; ; ; ; ; ;
06/05/2023

New Dartmouth Center Applies AI to Improve Health Outcomes

Article Excerpt: Dartmouth has created a Center for Precision Health and Artificial Intelligence (CPHAI ) to spur interdisciplinary research that can better leverage—as well as more safely and ethically deploy—biomedical data in assessing and treating patients and improving their health care outcomes…. “What makes CPHAI unique is its interdisciplinary and comprehensive approach to precision health and artificial intelligence, focusing not only on technological advancements but also on ethical and societal implications,” says Saeed Hassanpour, associate professor of biomedical data science, epidemiology, and computer science, who serves as the center’s inaugural director.

Full Article: https://tinyurl.com/2nxus3p7

Article Source: Dartmouth News

Posted in: Emerging Technologies, Methodologies & Analytics // Tagged: ; ; ; ; ; ;
05/30/2023

Predicting symptom response and engagement in a digital intervention among individuals with schizophrenia and related psychoses

Price GD, Heinz MV, Nemesure MD, McFadden J, Jacobson NC. Predicting symptom response and engagement in a digital intervention among individuals with schizophrenia and related psychoses. Front Psychiatry. 2022;13:807116. doi:10.3389/fpsyt.2022.807116

This study utilized data from a trial delivering a psychosocial smartphone app designed for patients with psychosis (App4Independence or A4i) to better understand personalized markers of digital intervention engagement and response. Machine learning models were applied to baseline data, app use data, and semi-structured interview data to predict response to change in symptoms, level of engagement, and qualitative impressions of the A4i app. Thirty-eight participants received the A4i app intervention for one month. Machine learning models were capable of moderately predicting participant engagement and experience with the app (r=0.39) as well as changes in psychosis symptom severity (r=0.32). Participants with high baseline interpersonal sensitivity, versus low, benefitted more from the A4i intervention in reducing symptom severity. Additionally, participants with lower baseline psychotic and obsessive-compulsive traits were predicted to benefit more. Higher baseline depression predicted both higher engagement and satisfaction with the app. These findings demonstrate the potential of predicting response to a digital intervention for psychosis using unique patient factors. This study further highlights the need to investigate individual response to and engagement with digital-based mental health interventions. Future research should consider how individual demographic characteristics influence engagement with a digital intervention.

Posted in: Cutting Edge Literature // Tagged: ; ; ; ; ;
05/09/2023

Can Machine Learning, Wearable Tech Help Treat Mental Health?

Article Excerpt: New research from the Icahn School of Medicine at Mount Sinai in New York indicated that using Apple Watch data, such as heart rate variability and resting heart rate, could assist in training machine learning models to determine patient well-being and resilience. According to the Centers for Disease Control and Prevention (CDC), over 20 percent of US adults have a mental illness. The CDC also noted that mental health diagnoses are some of the most common health conditions in the US. This latest study showed that wearable devices could help support patients with mental health diagnoses by collecting assistive data.

Full Article: https://tinyurl.com/3xubk4du

Article Source: Health IT Analytics

Posted in: Emerging Technologies // Tagged: ; ; ; ; ; ; ; ;
02/15/2023

ChatGPT Gets Dartmouth Talking

Article Excerpt: ChatGPT, OpenAI’s trending chatbot that generates conversational responses to user prompts through advanced artificial intelligence, has been busy since its launch in late November… “ChatGPT and other generative AI technologies have huge potential for—and will have huge effects on—education,” says Provost David Kotz ’86, the Pat and John Rosenwald Professor in the Department of Computer Science. “My hope is to provide immediate support to faculty and instructors to become familiar with the technology and its impacts, and then look further down the road to consider how we can leverage it as a pedagogical tool, recognizing that it will be part of the future of teaching, learning, scholarship, and work.”

Full Article: https://tinyurl.com/59hbkfzm

Article Source: Dartmouth News

Posted in: Emerging Technologies, Methodologies & Analytics // Tagged: ; ; ; ; ; ; ;
10/27/2022

Personalising Mental Health Care

Article Excerpt: Although researchers have made unprecedented progress in identifying ‘averaged’ or ‘population-level’ mechanisms of mental health disorders, these approaches have led to a drowning effect at an individual level where person-specific information is often lost if it doesn’t align with an averaged expectation. To bridge this gap between research and clinical practice, we have developed a novel individualised machine learning framework called Affinity Scores. By identifying personalised signatures that can be integrated into a clinician’s decision-making for each of their patients, Affinity Scores represent a fundamental shift in our approach to personalised psychiatry.

Full Article: https://tinyurl.com/mrcn2ayh

Article Source: Pursuit

Posted in: Emerging Technologies // Tagged: ; ; ; ; ;
09/30/2022

Can Smartphones Help Predict Suicide?

Article Excerpt: A unique research project is tracking hundreds of people at risk for suicide, using data from smartphones and wearable biosensors to identify periods of high danger — and intervene… In the field of mental health, few new areas generate as much excitement as machine learning, which uses computer algorithms to better predict human behavior. There is, at the same time, exploding interest in biosensors that can track a person’s mood in real time, factoring in music choices, social media posts, facial expression and vocal expression.

Full Article: https://tinyurl.com/4ay346zn

Article Source: The New York Times

Posted in: Emerging Technologies // Tagged: ; ; ; ; ; ; ; ;