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Tag: prediction
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: ; ; ; ; ; ; ; ;
03/23/2023

Spotting Opioid Overdoses Before They Happen, With AI

Article Excerpt: A Stony Brook University computer professor with an AI algorithm that detects substance abuse through language has refocused the impressive prediction technology on opioids – with startling results. Associate Computer Science Professor H. Andrew Schwartz is the senior author of a new study detailing the use of artificial intelligence to predict opioid mortalities. The work builds on Schwartz’s earlier success identifying high- and low-risk alcohol abuse via an AI application that interpreted language used in Facebook posts. This time, Schwartz and four other authors – including lead author Matthew Matero, an SBU computer-science student, and National Institute on Drug Abuse Data Scientist Salvatore Giorgi – hope to create some desperately needed “location-specific aid for the U.S. opioid crisis,” according to the abstract of an article published last week by the peer-reviewed open-access journal Npj Digital Medicine.

Full Article: https://tinyurl.com/6m4jwpd4

Article Source: Innovate LI

Posted in: Emerging Technologies, Methodologies & Analytics // Tagged: ; ; ; ; ; ;
02/07/2023

AI and Genetics Could Help Doctors Treat Alcohol Addiction, Research Shows

Article Excerpt: Imagine a patient has been diagnosed with alcohol use disorder, and their health care provider is reviewing medication options to help them curb their drinking. The provider asks the patient some basic questions, like alcohol cravings and stress levels, and collects a blood sample for genetic testing. A computer model uses this information to determine which medication would most likely support the patient with managing their alcohol use. With the help of the model, the provider gives a medication recommendation that is the best fit for their patient.

Full Article: https://tinyurl.com/58msbx3c

Article Source: Medical Xpress

Posted in: Emerging Technologies // Tagged: ; ; ; ; ; ; ;
11/07/2022

Weill Cornell Medicine Awarded NIH Grant to Address Opioid Health Crisis

Article Excerpt: Weill Cornell Medicine has been awarded a five-year, $8.1 million grant from the National Institutes of Health (NIH) to support economic analysis, simulation modeling and other research approaches to help stem the national opioid epidemic. “We’ve continued to witness the very disturbing increase in opioid overdoses over the last seven years, fueled by more fentanyl in the drug supply,” said principal investigator Dr. Bruce Schackman, the Saul P. Steinberg Distinguished Professor of Population Health Sciences and director of the Center for Health Economics of Treatment Interventions for Substance Use Disorder, HCB, and HIV (CHERISH) at Weill Cornell Medicine. “Opioid overdoses are now the highest they’ve ever been. That’s been a big driver of a greater national focus on treatment and interventions to reduce overdoses.”

Full Article: https://tinyurl.com/4px27edj

Article Source: Weill Cornell Medicine News

Posted in: Methodologies & Analytics // Tagged: ; ; ; ; ; ; ; ;
10/31/2022

Leveraging a Technology Accelerator to Drive Addiction Treatment Success

Article Excerpt: Effective treatments that lead to improved patient outcomes are what clinicians strive to provide for their patients across healthcare settings and specialties. But there may be many hurdles to treatment success depending on the condition, type of care required, or the way that patient data is used. This is especially true in behavioral health and addiction treatment, where finding and leveraging the drivers of treatment success can be hampered by limited technology and data analytics capabilities… The pervasiveness of SUD, along with the need for individualized treatments, can make it difficult for treatment centers and providers to gain insights into treatment success and improve practices. To meet this challenge, Cumberland Heights, a Tennessee-based drug and alcohol addiction treatment facility with 350 employees, 2,500 patients annually, and 20 locations, turned to a ‘technology accelerator’ platform. Nick Hayes, PhD, chief science officer at Cumberland Heights, sat down with HealthITAnalytics to discuss how the organization uses the cloud-based EMR software to better understand the ways in which unique patient predictors lead to better patient outcomes.

Full Article: https://tinyurl.com/2p9dn3zh

Article Source: Health IT Analytics

Posted in: Methodologies & Analytics // Tagged: ; ; ; ; ; ;