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Development of a natural language processing algorithm to detect chronic cough in electronic health records.

BMC pulmonary medicine
BACKGROUND: Chronic cough (CC) is difficult to identify in electronic health records (EHRs) due to the lack of specific diagnostic codes. We developed a natural language processing (NLP) model to identify cough in free-text provider notes in EHRs fro...

Machine learning in the identification, prediction and exploration of environmental toxicology: Challenges and perspectives.

Journal of hazardous materials
Over the past few decades, data-driven machine learning (ML) has distinguished itself from hypothesis-driven studies and has recently received much attention in environmental toxicology. However, the use of ML in environmental toxicology remains in t...

Application of Artificial Intelligence Methodologies to Chronic Wound Care and Management: A Scoping Review.

Advances in wound care
As the number of hard-to-heal wound cases rises with the aging of the population and the spread of chronic diseases, health care professionals struggle to provide safe and effective care to all their patients simultaneously. This study aimed at prov...

An Online Prognostic Application for Melanoma Based on Machine Learning and Statistics.

Journal of plastic, reconstructive & aesthetic surgery : JPRAS
BACKGROUND: Melanoma is a common cancer that causes a severe socioeconomic burden. Patients usually turn to plastic surgeons to determine their prognosis after surgery.

Deep Learning and Infrared Spectroscopy: Representation Learning with a β-Variational Autoencoder.

The journal of physical chemistry letters
Infrared (IR) spectra contain detailed and extensive information about the chemical composition and bonding environment in a sample. However, this information is difficult to extract from complex heterogeneous systems because of overlapping absorptio...

Machine learning and artificial intelligence in cardiac transplantation: A systematic review.

Artificial organs
BACKGROUND: This review aims to systematically evaluate the currently available evidence investigating the use of artificial intelligence (AI) and machine learning (ML) in the field of cardiac transplantation. Furthermore, based on the challenges ide...

DeepRF: A deep learning method for predicting metabolic pathways in organisms based on annotated genomes.

Computers in biology and medicine
The rapid increase of metabolomics has led to an increasing focus on metabolic pathway modeling and reconstruction. In particular, reconstructing an organism's metabolic network based on its genome sequence is a key challenge in systems biology. The ...

BPCNN: Bi-Point Input for Convolutional Neural Networks in Speaker Spoofing Detection.

Sensors (Basel, Switzerland)
We propose a method, called bi-point input, for convolutional neural networks (CNNs) that handle variable-length input features (e.g., speech utterances). Feeding input features into a CNN in a mini-batch unit requires that all features in each mini-...

Machine learning for contour classification in TG-263 noncompliant databases.

Journal of applied clinical medical physics
A large volume of medical data are labeled using nonstandardized nomenclature. Although efforts have been made by the American Association of Physicists in Medicine (AAPM) to standardize nomenclature through Task Group 263 (TG-263), there remain nonc...

Improved Prediction of Body Mass Index in Real-World Administrative Healthcare Claims Databases.

Advances in therapy
INTRODUCTION: To continue closing the gap between the predictive modeling and its real-world application, we report a new data-to-prediction pipeline that advanced the state-of-the-art predictive performance of body mass index (BMI) classifications b...