AIMC Topic: United States
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De-identification of free text data containing personal health information: a scoping review of reviews.
International journal of population data science
Dec 12, 2023
INTRODUCTION: Using data in research often requires that the data first be de-identified, particularly in the case of health data, which often include Personal Identifiable Information (PII) and/or Personal Health Identifying Information (PHII). Ther...
Comparison of Percutaneous Renal Access Between Robot-Assisted Fluoroscopy Guidance Using the Bi-Plane Method and Ultrasound Guidance: A Multicenter Randomized Control Benchtop Study.
Journal of endourology
Dec 11, 2023
To evaluate the efficacy of supine percutaneous renal access by robot-assisted (RA) fluoroscopy and ultrasound (US) guidance in terms of procedural outcomes and surgeon workload. We conducted a multicenter, randomized, controlled benchtop study inv...
Deciphering exogenous chemical carcinogenicity through interpretable deep learning: A novel approach for evaluating atmospheric pollutant hazards.
Journal of hazardous materials
Nov 25, 2023
Cancer remains a significant global health concern, with millions of deaths attributed to it annually. Environmental pollutants play a pivotal role in cancer etiology and contribute to the growing prevalence of this disease. The carcinogenic assessme...
A transformer-based deep learning approach for fairly predicting post-liver transplant risk factors.
Journal of biomedical informatics
Nov 20, 2023
Liver transplantation is a life-saving procedure for patients with end-stage liver disease. There are two main challenges in liver transplant: finding the best matching patient for a donor and ensuring transplant equity among different subpopulations...
Applications of Artificial Intelligence in Health Care Delivery.
Journal of medical systems
Nov 17, 2023
Health care costs now comprise nearly one-fifth of the United States' gross domestic product, with the last 25 years marked by rising administrative costs, a lack of labor productivity growth, and rising patient and physician dissatisfaction. Policy ...
Outcome prediction of methadone poisoning in the United States: implications of machine learning in the National Poison Data System (NPDS).
Drug and chemical toxicology
Nov 9, 2023
Methadone is an opioid receptor agonist with a high potential for abuse. The current study aimed to compare different machine learning models to predict the outcomes following methadone poisoning. This six-year retrospective longitudinal study utiliz...
ExplaiNAble BioLogical Age (ENABL Age): an artificial intelligence framework for interpretable biological age.
The lancet. Healthy longevity
Nov 6, 2023
BACKGROUND: Biological age is a measure of health that offers insights into ageing. The existing age clocks, although valuable, often trade off accuracy and interpretability. We introduce ExplaiNAble BioLogical Age (ENABL Age), a computational framew...
Deep Learning-Based Survival Analysis for Receiving a Steatotic Donor Liver Versus Waiting for a Standard Liver.
Transplantation proceedings
Oct 22, 2023
BACKGROUND: An emerging strategy to expand the donor pool is the use of a steatotic donor liver (SDLs; ≥ 30% macrosteatosis on biopsy). With the obesity epidemic and prevalence of nonalcoholic fatty liver disease, SDLs have been reported in 59% of al...
Identifying Potential Lyme Disease Cases Using Self-Reported Worldwide Tweets: Deep Learning Modeling Approach Enhanced With Sentimental Words Through Emojis.
Journal of medical Internet research
Oct 16, 2023
BACKGROUND: Lyme disease is among the most reported tick-borne diseases worldwide, making it a major ongoing public health concern. An effective Lyme disease case reporting system depends on timely diagnosis and reporting by health care professionals...
Application of Artificial Intelligence to Patient-Targeted Health Information on Kidney Stone Disease.
Journal of renal nutrition : the official journal of the Council on Renal Nutrition of the National Kidney Foundation
Oct 13, 2023
OBJECTIVE: The American Medical Association recommends health information to be written at a 6th grade level reading level. Our aim was to determine whether Artificial Intelligence can outperform the existing health information on kidney stone preven...
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