AIMC Topic: Databases, Factual

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The extraction of complex relationships and their conversion to biological expression language (BEL) overview of the BioCreative VI (2017) BEL track.

Database : the journal of biological databases and curation
Knowledge of the molecular interactions of biological and chemical entities and their involvement in biological processes or clinical phenotypes is important for data interpretation. Unfortunately, this knowledge is mostly embedded in the literature ...

Deep CNN models for pulmonary nodule classification: Model modification, model integration, and transfer learning.

Journal of X-ray science and technology
BACKGROUND: Deep learning has made spectacular achievements in analysing natural images, but it faces challenges for medical applications partly due to inadequate images.

Episodic-Memory Performance in Machine Learning Modeling for Predicting Cognitive Health Status Classification.

Journal of Alzheimer's disease : JAD
BACKGROUND: Memory dysfunction is characteristic of aging and often attributed to Alzheimer's disease (AD). An easily administered tool for preliminary assessment of memory function and early AD detection would be integral in improving patient manage...

Information Adapted Machine Learning Models for Prediction in Clinical Workflow.

Studies in health technology and informatics
BACKGROUND: In a database of electronic health records, the amount of available information varies widely between patients. In a real-time prediction scenario, a machine learning model may receive limited information for some patients.

Engineering Bias in AI.

IEEE pulse
After working at Apple designing circuits and signal processing algorithms for products including the first iPad, Timnit Gebru (Figure 1) received her Ph.D. from the Stanford Artificial Intelligence Laboratory in the area of computer vision. She rece...

PLATYPUS: A Multiple-View Learning Predictive Framework for Cancer Drug Sensitivity Prediction.

Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing
Cancer is a complex collection of diseases that are to some degree unique to each patient. Precision oncology aims to identify the best drug treatment regime using molecular data on tumor samples. While omics-level data is becoming more widely availa...

The Effectiveness of Multitask Learning for Phenotyping with Electronic Health Records Data.

Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing
Electronic phenotyping is the task of ascertaining whether an individual has a medical condition of interest by analyzing their medical record and is foundational in clinical informatics. Increasingly, electronic phenotyping is performed via supervis...

Learning Contextual Hierarchical Structure of Medical Concepts with Poincairé Embeddings to Clarify Phenotypes.

Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing
Biomedical association studies are increasingly done using clinical concepts, and in particular diagnostic codes from clinical data repositories as phenotypes. Clinical concepts can be represented in a meaningful, vector space using word embedding mo...

Breast mass detection and diagnosis using fused features with density.

Journal of X-ray science and technology
BACKGROUND: The morbidity of breast cancer has been increased in these years and ranked the first of all female diseases. Computer-aided diagnosis techniques for mammograms can help radiologists find early breast lesions. In mammograms, the degree of...

How to Develop a Drug Target Ontology: KNowledge Acquisition and Representation Methodology (KNARM).

Methods in molecular biology (Clifton, N.J.)
Technological advancements in many fields have led to huge increases in data production, including data volume, diversity, and the speed at which new data is becoming available. In accordance with this, there is a lack of conformity in the ways data ...