AIMC Topic: Workflow

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WEADE: A workflow for enrichment analysis and data exploration.

PloS one
Data analysis based on enrichment of Gene Ontology terms has become an important step in exploring large gene or protein expression datasets and several stand-alone or web tools exist for that purpose. However, a comprehensive and consistent analysis...

Predictive classifier models built from natural products with antimalarial bioactivity using machine learning approach.

PloS one
In view of the vast number of natural products with potential antiplasmodial bioactivity and cost of conducting antiplasmodial bioactivity assays, it may be judicious to learn from previous antiplasmodial bioassays and predict bioactivity of these na...

Increasing workflow development speed and reproducibility with Vectools.

F1000Research
Despite advances in bioinformatics, custom scripts remain a source of difficulty, slowing workflow development and hampering reproducibility. Here, we introduce Vectools, a command-line tool-suite to reduce reliance on custom scripts and improve repr...

Abdominal, multi-organ, auto-contouring method for online adaptive magnetic resonance guided radiotherapy: An intelligent, multi-level fusion approach.

Artificial intelligence in medicine
BACKGROUND: Manual contouring remains the most laborious task in radiation therapy planning and is a major barrier to implementing routine Magnetic Resonance Imaging (MRI) Guided Adaptive Radiation Therapy (MR-ART). To address this, we propose a new ...

MfeCNN: Mixture Feature Embedding Convolutional Neural Network for Data Mapping.

IEEE transactions on nanobioscience
Data mapping plays an important role in data integration and exchanges among institutions and organizations with different data standards. However, traditional rule-based approaches and machine learning methods fail to achieve satisfactory results fo...

Simulation of patient flow in multiple healthcare units using process and data mining techniques for model identification.

Journal of biomedical informatics
INTRODUCTION: An approach to building a hybrid simulation of patient flow is introduced with a combination of data-driven methods for automation of model identification. The approach is described with a conceptual framework and basic methods for comb...

Label-indicator morpheme growth on LSTM for Chinese healthcare question department classification.

Journal of biomedical informatics
BACKGROUND: Current Chinese medicine has an urgent demand for convenient medical services. When facing a large number of patients, understanding patients' questions automatically and precisely is useful. Different from the high professional medical t...

Approximate dynamic programming approaches for appointment scheduling with patient preferences.

Artificial intelligence in medicine
During the appointment booking process in out-patient departments, the level of patient satisfaction can be affected by whether or not their preferences can be met, including the choice of physicians and preferred time slot. In addition, because the ...