AIMC Topic: Databases, Factual

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Improved SSD network for accurate detection of optic disc and fovea and application in excyclotropia screening.

Journal of the Optical Society of America. A, Optics, image science, and vision
The detection of the optic disc (OD) and fovea is essential to many automatic diagnosis systems for retinal diseases. The single shot multibox detector (SSD) can generate predictions from feature maps of various resolutions, which has not been introd...

Phenotypic clustering of heart failure with preserved ejection fraction reveals different rates of hospitalization.

Journal of cardiovascular medicine (Hagerstown, Md.)
AIMS: Approximately 50% of patients with heart failure have preserved (≥50%) ejection fraction (HFpEF). Improved understanding of the phenotypic heterogeneity of HFpEF might facilitate development of targeted therapies and interventions.

Synergistic Drug Combination Prediction by Integrating Multiomics Data in Deep Learning Models.

Methods in molecular biology (Clifton, N.J.)
Intrinsic and acquired drug resistance is a major challenge in cancer therapy. Synergistic drug combinations could help to overcome drug resistance. However, the number of possible drug combinations is enormous, and it is infeasible to experimentally...

Using Neural Networks for Relation Extraction from Biomedical Literature.

Methods in molecular biology (Clifton, N.J.)
Using different sources of information to support automated extracting of relations between biomedical concepts contributes to the development of our understanding of biological systems. The primary comprehensive source of these relations is biomedic...

Machine Learning Applied to Registry Data: Development of a Patient-Specific Prediction Model for Blood Transfusion Requirements During Craniofacial Surgery Using the Pediatric Craniofacial Perioperative Registry Dataset.

Anesthesia and analgesia
BACKGROUND: Craniosynostosis is the premature fusion of ≥1 cranial sutures and often requires surgical intervention. Surgery may involve extensive osteotomies, which can lead to substantial blood loss. Currently, there are no consensus recommendation...

Democratizing EHR analyses with FIDDLE: a flexible data-driven preprocessing pipeline for structured clinical data.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: In applying machine learning (ML) to electronic health record (EHR) data, many decisions must be made before any ML is applied; such preprocessing requires substantial effort and can be labor-intensive. As the role of ML in health care gro...

Biomedical named entity recognition and linking datasets: survey and our recent development.

Briefings in bioinformatics
Natural language processing (NLP) is widely applied in biological domains to retrieve information from publications. Systems to address numerous applications exist, such as biomedical named entity recognition (BNER), named entity normalization (NEN) ...

An omics perspective on drug target discovery platforms.

Briefings in bioinformatics
The drug discovery process starts with identification of a disease-modifying target. This critical step traditionally begins with manual investigation of scientific literature and biomedical databases to gather evidence linking molecular target to di...

Meta-analysis of voice disorders databases and applied machine learning techniques.

Mathematical biosciences and engineering : MBE
Voice disorders are pathological conditions that directly affect voice production. Computer based diagnosis may play a major role in the early detection and in tracking and even development of efficient pathological speech diagnosis, based on a comp...

[Pathological diagnosis of lung cancer based on deep transfer learning].

Zhonghua bing li xue za zhi = Chinese journal of pathology
To establish an artificial intelligence (AI)-assisted diagnostic system for lung cancer via deep transfer learning. The researchers collected 519 lung pathologic slides from 2016 to 2019, covering various lung tissues, including normal tissues, ade...