AIMC Topic: Adult

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Using artificial intelligence to optimize delivery of weight loss treatment: Protocol for an efficacy and cost-effectiveness trial.

Contemporary clinical trials
Gold standard behavioral weight loss (BWL) is limited by the availability of expert clinicians and high cost of delivery. The artificial intelligence (AI) technique of reinforcement learning (RL) is an optimization solution that tracks outcomes assoc...

Pediatric Automatic Sleep Staging: A Comparative Study of State-of-the-Art Deep Learning Methods.

IEEE transactions on bio-medical engineering
BACKGROUND: Despite the tremendous prog- ress recently made towards automatic sleep staging in adults, it is currently unknown if the most advanced algorithms generalize to the pediatric population, which displays distinctive characteristics in overn...

Relative Validation of an Artificial Intelligence-Enhanced, Image-Assisted Mobile App for Dietary Assessment in Adults: Randomized Crossover Study.

Journal of medical Internet research
BACKGROUND: Thorough dietary assessment is essential to obtain accurate food and nutrient intake data yet challenging because of the limitations of current methods. Image-based methods may decrease energy underreporting and increase the validity of s...

A Pilot Machine Learning Study Using Trauma Admission Data to Identify Risk for High Length of Stay.

Surgical innovation
INTRODUCTION: Trauma patients have diverse resource needs due to variable mechanisms and injury patterns. The aim of this study was to build a tool that uses only data available at time of admission to predict prolonged hospital length of stay (LOS).

Personalized prediction of optimal water intake in adult population by blended use of machine learning and clinical data.

Scientific reports
Growing evidence suggests that sustained concentrated urine contributes to chronic metabolic and kidney diseases. Recent results indicate that a daily urinary concentration of 500 mOsm/kg reflects optimal hydration. This study aims at providing perso...

Prediction of gender from longitudinal MRI data via deep learning on adolescent data reveals unique patterns associated with brain structure and change over a two-year period.

Journal of neuroscience methods
Deep learning algorithms for predicting neuroimaging data have shown considerable promise in various applications. Prior work has demonstrated that deep learning models that take advantage of the data's 3D structure can outperform standard machine le...

Recognition of the Effect of Vocal Exercises by Fuzzy Triangular Naive Bayes, a Machine Learning Classifier: A Preliminary Analysis.

Journal of voice : official journal of the Voice Foundation
OBJECTIVES: Machine learning (ML) methods allow the development of expert systems for pattern recognition and predictive analysis of intervention outcomes. It has been used in Voice Sciences, mainly to discriminate between healthy and dysphonic voice...

Fully automated CT-based adiposity assessment: comparison of the L1 and L3 vertebral levels for opportunistic prediction.

Abdominal radiology (New York)
PURPOSE: The purpose of this study is to compare fully automated CT-based measures of adipose tissue at the L1 level versus the standard L3 level for predicting mortality, which would allow for use at both chest (L1) and abdominal (L3) CT.

Deep Learning-based calculation of patient size and attenuation surrogates from localizer Image: Toward personalized chest CT protocol optimization.

European journal of radiology
PURPOSE: Extracting water equivalent diameter (DW), as a good descriptor of patient size, from the CT localizer before the spiral scan not only minimizes truncation errors due to the limited scan field-of-view but also enables prior size-specific dos...

Overtriage, Undertriage, and Value of Care after Major Surgery: An Automated, Explainable Deep Learning-Enabled Classification System.

Journal of the American College of Surgeons
BACKGROUND: In single-institution studies, overtriaging low-risk postoperative patients to ICUs has been associated with a low value of care; undertriaging high-risk postoperative patients to general wards has been associated with increased mortality...