AIMC Topic: Algorithms

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Identify and monitor clinical variation using machine intelligence: a pilot in colorectal surgery.

Journal of clinical monitoring and computing
Standardized clinical pathways are useful tool to reduce variation in clinical management and may improve quality of care. However the evidence supporting a specific clinical pathway for a patient or patient population is often imperfect limiting ado...

Joint Weakly and Semi-Supervised Deep Learning for Localization and Classification of Masses in Breast Ultrasound Images.

IEEE transactions on medical imaging
We propose a framework for localization and classification of masses in breast ultrasound images. We have experimentally found that training convolutional neural network-based mass detectors with large, weakly annotated datasets presents a non-trivia...

An improved stability result for delayed Takagi-Sugeno fuzzy Cohen-Grossberg neural networks.

Neural networks : the official journal of the International Neural Network Society
This work proposes a novel and improved delay independent global asymptotic stability criterion for delayed Takagi-Sugeno (T-S) fuzzy Cohen-Grossberg neural networks exploiting a suitable fuzzy-type Lyapunov functional in the presence of the nondecre...

SiRNA silencing efficacy prediction based on a deep architecture.

BMC genomics
BACKGROUND: Small interfering RNA (siRNA) can be used to post-transcriptional gene regulation by knocking down targeted genes. In functional genomics, biomedical research and cancer therapeutics, siRNA design is a critical research topic. Various com...

Deep learning-based transcriptome data classification for drug-target interaction prediction.

BMC genomics
BACKGROUND: The ability to predict the interaction of drugs with target proteins is essential to research and development of drug. However, the traditional experimental paradigm is costly, and previous in silico prediction paradigms have been impeded...

Flexible Learning-Free Segmentation and Reconstruction of Neural Volumes.

Scientific reports
Imaging is a dominant strategy for data collection in neuroscience, yielding stacks of images that often scale to gigabytes of data for a single experiment. Machine learning algorithms from computer vision can serve as a pair of virtual eyes that tir...

Machine Learning for detection of viral sequences in human metagenomic datasets.

BMC bioinformatics
BACKGROUND: Detection of highly divergent or yet unknown viruses from metagenomics sequencing datasets is a major bioinformatics challenge. When human samples are sequenced, a large proportion of assembled contigs are classified as "unknown", as conv...

Creation of a Robust and Generalizable Machine Learning Classifier for Patient Ventilator Asynchrony.

Methods of information in medicine
BACKGROUND: As healthcare increasingly digitizes, streaming waveform data is being made available from an variety of sources, but there still remains a paucity of performant clinical decision support systems. For example, in the intensive care unit (...

Is Multiclass Automatic Text De-Identification Worth the Effort?

Methods of information in medicine
OBJECTIVES: Automatic de-identification to remove protected health information (PHI) from clinical text can use a "binary" model that replaces redacted text with a generic tag (e.g., ""), or can use a "multiclass" model that retains more class i...

Learning to Detect Cognitive Impairment through Digital Games and Machine Learning Techniques.

Methods of information in medicine
OBJECTIVE: Alzheimer's disease (AD) is one of the most prevalent diseases among the adult population. The early detection of Mild Cognitive Impairment (MCI), which may trigger AD, is essential to slow down the cognitive decline process.