Mar 07,2023

Using ChatGPT to write patient clinic letters

AI, like ChatGPT, has the potential to produce high quality clinical letters that are comprehendible by patients while improving efficiency, consistency, accuracy, patient satisfaction, and deliver cost savings to a health-care system. In this Comment researchers describe the early adoption and evaluation of ChatGPT-generated clinical letters to patients with limited clinical input. They created a series of different clinical communication scenarios that covered the remit of a clinicians' skin cancer practice. 38 hypothetical clinical scenarios were created, seven of which pertained to BCC, 11 to squamous cell carcinoma (SCC), and 20 to malignant melanoma. Overall, the readability scores suggest that the text might be suitable for a varying reading ability, and the mean readability age for the generated letters was at a USA ninth grade (aged 14–15 years) and considered by the US Department of Health and Human Services as average difficulty.

CLINICAL STUDY

#ai/software

#chatbot

View Analyst & Ambassador Comments
Go to original news
Feb 03,2023

Sussex Researchers use AI to Personalise Cancer Patient Treatments

Researchers at the University of Sussex are using Artificial Intelligence (AI) technology to analyse different types of cancer cells to understand different gene dependencies, and to identify genes that are critical to a cell's survival. Sussex researchers have done this by developing a prediction algorithm that works out which genes are essential in the cell, by analysing the genetic changes in the tumour. This can be used to identify actionable targets that in time could guide oncologists to personalise cancer patient treatments.

CLINICAL STUDY

#ai/software

View Analyst & Ambassador Comments
Go to original news
Jan 26,2023

AI Analysis of Cancer Mutations may Improve Therapy

Cancer has many faces - no wonder, then, that the range of cancer-causing mutations is huge as well. The totality of such genomic alterations in an individual is what experts call a "mutational landscape." These landscapes differ from one another depending on the type of cancer. Somatic structural variants (SVs) have been shown to account for more than half of all cancer-driving mutations. These are those mutations in cells that emerge over the course of life. Although somatic SVs play a crucial role in cancer development, relatively little is known about them. That's changing thanks to new research findings, which Dr. Ashley Sanders's recently published in the journal Nature Biotechnology along with the European Molecular Biology Laboratory (EMBL). "We developed a computational analysis method to detect and identify the functional effects of somatic SVs," she reports. This enabled the team to understand the molecular consequences of individual somatic mutations in different leukemia patients, giving them new insights into the mutation-specific alterations. Sanders says it may also be possible to use these findings to develop therapies that target the mutated cells, adding that “they open up exciting new avenues for personalized medicine."

CLINICAL STUDY

#ai/software

View Analyst & Ambassador Comments
Go to original news
Jan 23,2023

A Blood Test for Cancer Shows Promise Thanks to Machine Learning

A team of researchers at the University of Wisconsin­-Madison has successfully combined genomics with machine learning in the quest to develop accessible tests that allow earlier detection of cancer. In a study published this week in Science Translational Medicine and led by Muhammed Murtaza, professor of surgery at the UW School of Medicine and Public Health, researchers used a machine-learning model to examine blood plasma for DNA fragments from cancer cells. The technique, which uses readily available lab materials, detected cancers at an early stage among most of the samples they studied.

CLINICAL STUDY

#ai/software

View Analyst & Ambassador Comments
Go to original news
Jan 13,2023

AI Tool Developed to Predict Risk of Lung Cancer

As rates of lung cancer climb among non-smokers, new strategies are needed to screen and accurately predict lung cancer risk across a wider population. A study led by investigators from the Mass General Cancer Center, a member of Mass General Brigham, in collaboration with researchers at the Massachusetts Institute of Technology (MIT), developed and tested an artificial intelligence tool known as Sybil. Based on analyses of Low-dose chest computed tomography (LDCT) scans from patients in the U.S. and Taiwan, Sybil accurately predicted the risk of lung cancer for individuals with or without a significant smoking history. Results are published in the Journal of Clinical Oncology.

CLINICAL STUDY

#ai/software

View Analyst & Ambassador Comments
Go to original news
Apr 19,2018

DIABEO App Software and Telemedicine Versus Usual Follow-Up in the Treatment of Diabetic Patients: Protocol for the TELESAGE Randomized Controlled Trial

Self-management of diabetes minimizes the risk of macrovascular and microvascular complications, but understanding and/or adherence to self-management recommendations is often suboptimal. The researchers present the protocol for a new study TELESAGE, a multicenter, double-randomized, open-label, three parallel–arms study, conducted in approximately 100 centers in France, in a larger population of diabetic patients with poorly controlled basal-bolus insulin levels. DIABEO is a smartphone app used to calculate bolus insulin doses. A previous study (TELEDIAB 1) showed that the use of DIABEO was associated with a significant improvement in glycemic control in patients with poorly controlled type 1 diabetes mellitus, particularly when combined with teleconsultations with physicians. The primary objective of TELESAGE will be to investigate the effect of the DIABEO telemedicine system versus usual follow-up, with respect to improvements in the glycated hemoglobin levels of approximately 696 diabetic patients with poorly controlled basal-bolus insulin levels.

CLINICAL STUDY

#telehealth

#mobile app

View Analyst & Ambassador Comments
Go to original news
May 18,2023

Results from LifeScan's Study Showing People with Type 2 Diabetes Achieved Clinically Significant Improved Glycemic Control with One to Two Blood Glucose Checks Per Day Using SBGM and Mobile App

LifeScan announced that results from the study of real-world evidence Sustained Improvements in Readings In-Range Using an Advanced Bluetooth® Connected Blood Glucose Meter and a Mobile Diabetes App: Real-World Evidence from more than 55,000 People with Diabetes have been published in the peer-reviewed journal Diabetes Therapy. Using real-world data from more than 55,000 people with diabetes (PWD), this study aimed to understand if using the OneTouch Reveal® (OTR) mobile app with the OneTouch Verio Reflect® (OTVR) meter – synced via Bluetooth® wireless technology – could support sustained glycemic improvements for 180 days in people with type 1 diabetes (PwT1D) or type 2 diabetes (PwT2D). The real-world data demonstrated that PwT2D saw sustained, clinically significant improvements when engaging in just one to two OTR mobile app sessions per week, and performing one to two OTVR meter checks per day, over 180 days (n=3,563), including: Improved glucose readings in range in PwT2D by +12.0 percentage points; and Reduced hyperglycemic readings (>180 mg/dL) by -12.2 percentage points in PwT2D.

CLINICAL STUDY

#bgm

#mobile app

View Analyst & Ambassador Comments
Go to original news
Feb 21,2023

Lark Health’s Artificial Intelligence (AI) Heart Health Program Significantly Improves Cardiac Self-Efficacy

Lark Health, a leading digital care company for the prevention and management of chronic conditions, today announced key results from its pilot study surrounding its Artificial Intelligence (AI)-powered Heart Health program, which helps patients prevent and manage heart disease by targeting Cardiovascular Disease (CVD) risk factors. The study, “Cardiac Self-Efficacy Improvement in a Digital Health Pilot Program for Heart Health” found that, on average, study participants increased their Cardiac Self-Efficacy (CSE) score by 12.93 percent, the first digital care solution to show CSE improvement. In collaboration with Roche Diagnostics, the 90-day pilot study first helped participants identify their own personal risks for developing cardiovascular disease, and then provided them with AI-powered care coaching and educational lessons focused on behaviors that reduce those risks and promote better heart health. The CSE study results will be presented at The Society of Behavioral Medicine's 44th Annual Meeting & Scientific Sessions in Phoenix, AZ, from April 26–29, 2023.

CLINICAL STUDY

#coaching

#mobile app

View Analyst & Ambassador Comments
Go to original news
May 09,2023

Sanofi research demonstrates 9.3% reduction in all-cause healthcare resource utilization rates, including 23.5% decrease in hospitalization for Dario users

DarioHealth announced today the presentation of research at ISPOR 2023 demonstrating significant reductions in healthcare resource utilization for Dario users with type 2 diabetes compared to non-users, the first study completed by Sanofi U.S. under its strategic agreement with Dario. This study used de-identified user data from Dario and claims data, through tokenization, to build highly comparable groups through a meticulous matching method that matched 2,445 Dario users with 7,334 non-users. The difference-in-difference method was used to analyze changes between the start and end of the study period in each group and between Dario user and non-user groups, on predefined primary and secondary endpoints. The results demonstrate a statistically significant 9.3% reduction in all-cause Heath Care Resource Utilization (HCRU), including a 23.5% reduction in hospitalizations, in Dario users after 12 months.

CLINICAL STUDY

#dtx

View Analyst & Ambassador Comments
Go to original news
May 09,2023

Study backs Fitterfly digital therapeutic for diabetes management

New research published in JMIR Diabetes demonstrated the real-world effectiveness of the Fitterfly Diabetes digital therapeutic program. The study analyzed de-identified data of 109 participants with type 2 diabetes. The program features three phases. First, it observes participants’ CGM readings for one week. Next, they received diet- and exercise-based interventions through the Fitterfly app and coaches. Finally, researchers tracked whether the participants sustained their new lifestyle modifications over three months. Researchers say about 85% of all participants observed an average reduction of 1.2% in HbA1c levels. The study also found that participants who engaged more with the Fitterfly app presented improved clinical outcomes.

CLINICAL STUDY

#coaching

#mobile app

#dtx

View Analyst & Ambassador Comments
Go to original news
Subscribe to CLINICAL STUDY