AIMC Topic: Machine Learning

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Multiple Machine Learning Based-Chemoinformatics Models for Identification of Histone Acetyl Transferase Inhibitors.

Molecular informatics
The histone acetyl transferase (HAT) are involved in acetylation of histones that lead to transcription activation in numerous gene regulatory mechanisms. There are very few GCN5 HAT inhibitors reported despite of their role in cancer progression. In...

Advances in industrial biopharmaceutical batch process monitoring: Machine-learning methods for small data problems.

Biotechnology and bioengineering
Biopharmaceutical manufacturing comprises of multiple distinct processing steps that require effective and efficient monitoring of many variables simultaneously in real-time. The state-of-the-art real-time multivariate statistical batch process monit...

Replicating human expertise of mechanical ventilation waveform analysis in detecting patient-ventilator cycling asynchrony using machine learning.

Computers in biology and medicine
BACKGROUND: - Acute respiratory failure is one of the most common problems encountered in intensive care units (ICU) and mechanical ventilation is the mainstay of supportive therapy for such patients. A mismatch between ventilator delivery and patien...

Effective deep learning training for single-image super-resolution in endomicroscopy exploiting video-registration-based reconstruction.

International journal of computer assisted radiology and surgery
PURPOSE: Probe-based confocal laser endomicroscopy (pCLE) is a recent imaging modality that allows performing in vivo optical biopsies. The design of pCLE hardware, and its reliance on an optical fibre bundle, fundamentally limits the image quality w...

EMR-based medical knowledge representation and inference via Markov random fields and distributed representation learning.

Artificial intelligence in medicine
OBJECTIVE: Electronic medical records (EMRs) contain medical knowledge that can be used for clinical decision support (CDS). Our objective is to develop a general system that can extract and represent knowledge contained in EMRs to support three CDS ...

A machine learning based framework to identify and classify long terminal repeat retrotransposons.

PLoS computational biology
Transposable elements (TEs) are repetitive nucleotide sequences that make up a large portion of eukaryotic genomes. They can move and duplicate within a genome, increasing genome size and contributing to genetic diversity within and across species. A...

Unsupervised versus Supervised Identification of Prognostic Factors in Patients with Localized Retroperitoneal Sarcoma: A Data Clustering and Mahalanobis Distance Approach.

BioMed research international
The aim of this report is to unveil specific prognostic factors for retroperitoneal sarcoma (RPS) patients by univariate and multivariate statistical techniques. A phase I-II study on localized RPS treated with high-dose ifosfamide and radiotherapy f...

Constructing Temporally Extended Actions through Incremental Community Detection.

Computational intelligence and neuroscience
Hierarchical reinforcement learning works on temporally extended actions or skills to facilitate learning. How to automatically form such abstraction is challenging, and many efforts tackle this issue in the options framework. While various approache...

Malay sentiment analysis based on combined classification approaches and Senti-lexicon algorithm.

PloS one
Sentiment analysis techniques are increasingly exploited to categorize the opinion text to one or more predefined sentiment classes for the creation and automated maintenance of review-aggregation websites. In this paper, a Malay sentiment analysis c...

Making Individual Prognoses in Psychiatry Using Neuroimaging and Machine Learning.

Biological psychiatry. Cognitive neuroscience and neuroimaging
Psychiatric prognosis is a difficult problem. Making a prognosis requires looking far into the future, as opposed to making a diagnosis, which is concerned with the current state. During the follow-up period, many factors will influence the course of...