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Deep learning for prediction of colorectal cancer outcome: a discovery and validation study.

Lancet (London, England)
BACKGROUND: Improved markers of prognosis are needed to stratify patients with early-stage colorectal cancer to refine selection of adjuvant therapy. The aim of the present study was to develop a biomarker of patient outcome after primary colorectal ...

Innovative Identification of Substance Use Predictors: Machine Learning in a National Sample of Mexican Children.

Prevention science : the official journal of the Society for Prevention Research
Machine learning provides a method of identifying factors that discriminate between substance users and non-users potentially improving our ability to match need with available prevention services within context with limited resources. Our aim was to...

Validation of Deep Convolutional Neural Network-based algorithm for detection of diabetic retinopathy - Artificial intelligence versus clinician for screening.

Indian journal of ophthalmology
PURPOSE: Deep learning is a newer and advanced subfield in artificial intelligence (AI). The aim of our study is to validate a machine-based algorithm developed based on deep convolutional neural networks as a tool for screening to detect referable d...

Medios- An offline, smartphone-based artificial intelligence algorithm for the diagnosis of diabetic retinopathy.

Indian journal of ophthalmology
PURPOSE: An observational study to assess the sensitivity and specificity of the Medios smartphone-based offline deep learning artificial intelligence (AI) software to detect diabetic retinopathy (DR) compared with the image diagnosis of ophthalmolog...

Adverse drug event rates in pediatric pulmonary hypertension: a comparison of real-world data sources.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: Real-world data (RWD) are increasingly used for pharmacoepidemiology and regulatory innovation. Our objective was to compare adverse drug event (ADE) rates determined from two RWD sources, electronic health records and administrative claim...

Can Machine Learning Improve Screening for Targeted Delinquency Prevention Programs?

Prevention science : the official journal of the Society for Prevention Research
The cost-effectiveness of targeted delinquency prevention programs for children depends on the accuracy of the screening process. Screening accuracy is often poor, resulting in wasted resources and missed opportunities to avert negative outcomes. Thi...

A Robot-Based Play-Drama Intervention May Improve the Joint Attention and Functional Play Behaviors of Chinese-Speaking Preschoolers with Autism Spectrum Disorder: A Pilot Study.

Journal of autism and developmental disorders
Children with autism spectrum disorder (ASD) have deficits in joint attention and play behaviors. We examined whether a robot-based play-drama intervention would promote these skills. Chinese-speaking preschool children were randomly assigned to an i...