AIMC Topic: Humans

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DI++: A deep learning system for patient condition identification in clinical notes.

Artificial intelligence in medicine
Accurately recording a patient's medical conditions in an EHR system is the basis of effectively documenting patient health status, coding for billing, and supporting data-driven clinical decision making. However, patient conditions are often not ful...

AI in predicting COPD in the Canadian population.

Bio Systems
Chronic obstructive pulmonary disease (COPD) is a progressive lung disease that produces non-reversible airflow limitations. Approximately 10% of Canadians aged 35 years or older are living with COPD. Primary care is often the first contact an indivi...

Development and Practical Implementation of a Deep Learning-Based Pipeline for Automated Pre- and Postoperative Glioma Segmentation.

AJNR. American journal of neuroradiology
BACKGROUND AND PURPOSE: Quantitative volumetric segmentation of gliomas has important implications for diagnosis, treatment, and prognosis. We present a deep-learning model that accommodates automated preoperative and postoperative glioma segmentatio...

Unsupervised learning of cross-modal mappings in multi-omics data for survival stratification of gastric cancer.

Future oncology (London, England)
This study presents a survival stratification model based on multi-omics integration using bidirectional deep neural networks (BiDNNs) in gastric cancer. Based on the survival-related representation features yielded by BiDNNs through integrating tr...

Automatic upper airway segmentation in static and dynamic MRI via anatomy-guided convolutional neural networks.

Medical physics
PURPOSE: Upper airway segmentation on MR images is a prerequisite step for quantitatively studying the anatomical structure and function of the upper airway and surrounding tissues. However, the complex variability of intensity and shape of anatomica...

Generative Chemical Transformer: Neural Machine Learning of Molecular Geometric Structures from Chemical Language via Attention.

Journal of chemical information and modeling
Discovering new materials better suited to specific purposes is an important issue in improving the quality of human life. Here, a neural network that creates molecules that meet some desired multiple target conditions based on a deep understanding o...

Robotic high-throughput biomanufacturing and functional differentiation of human pluripotent stem cells.

Stem cell reports
Efficient translation of human induced pluripotent stem cells (hiPSCs) requires scalable cell manufacturing strategies for optimal self-renewal and functional differentiation. Traditional manual cell culture is variable and labor intensive, posing ch...

Real-Time Arrhythmia Detection Using Hybrid Convolutional Neural Networks.

Journal of the American Heart Association
Background Accurate detection of arrhythmic events in the intensive care units (ICU) is of paramount significance in providing timely care. However, traditional ICU monitors generate a high rate of false alarms causing alarm fatigue. In this work, we...

Machine Learning and Bioinformatics Framework Integration to Potential Familial DCM-Related Markers Discovery.

Genes
OBJECTIVES: Dilated cardiomyopathy (DCM) is characterized by a specific transcriptome. Since the DCM molecular network is largely unknown, the aim was to identify specific disease-related molecular targets combining an original machine learning (ML) ...

A machine learning pipeline revealing heterogeneous responses to drug perturbations on vascular smooth muscle cell spheroid morphology and formation.

Scientific reports
Machine learning approaches have shown great promise in biology and medicine discovering hidden information to further understand complex biological and pathological processes. In this study, we developed a deep learning-based machine learning algori...