AIMC Topic: Information Storage and Retrieval

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Achievability to Extract Specific Date Information for Cancer Research.

AMIA ... Annual Symposium proceedings. AMIA Symposium Mar 4, 2020
Accurate identification of temporal information such as date is crucial for advancing cancer research which often requires precise date information associated with related cancer events. However, there is a gap for existing natural language processin...
Time Humans Multiple Myeloma Electronic Health Records Information Storage and Retrieval Biomedical Research Natural Language Processing Data Collection Medical Oncology Neoplasms Lung Neoplasms
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Using Natural Language Processing to improve EHR Structured Data-based Surgical Site Infection Surveillance.

AMIA ... Annual Symposium proceedings. AMIA Symposium Mar 4, 2020
Surgical Site Infection surveillance in healthcare systems is labor intensive and plagued by underreporting as current methodology relies heavily on manual chart review. The rapid adoption of electronic health records (EHRs) has the potential to allo...
Surgical Wound Infection Information Storage and Retrieval Sensitivity and Specificity Algorithms Humans Logistic Models Support Vector Machine Electronic Health Records Decision Trees Machine Learning Natural Language Processing
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Polyp fingerprint: automatic recognition of colorectal polyps' unique features.

Surgical endoscopy Feb 11, 2020
BACKGROUND: Content-based image retrieval (CBIR) is an application of machine learning used to retrieve images by similarity on the basis of features. Our objective was to develop a CBIR system that could identify images containing the same polyp ('p...
Humans Colonic Polyps Image Interpretation, Computer-Assisted Information Storage and Retrieval Machine Learning Colonoscopy
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Inorganic Materials Synthesis Planning with Literature-Trained Neural Networks.

Journal of chemical information and modeling Jan 28, 2020
Leveraging new data sources is a key step in accelerating the pace of materials design and discovery. To complement the strides in synthesis planning driven by historical, experimental, and computed data, we present an automated, unsupervised method ...
Information Storage and Retrieval Chemistry Techniques, Synthetic Language Natural Language Processing Neural Networks, Computer
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Combinatorial feature embedding based on CNN and LSTM for biomedical named entity recognition.

Journal of biomedical informatics Jan 28, 2020
With the rapid advancement of technology and the necessity of processing large amounts of data, biomedical Named Entity Recognition (NER) has become an essential technique for information extraction in the biomedical field. NER, which is a sequence-l...
Neural Networks, Computer Information Storage and Retrieval Language Machine Learning
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Multicenter Computer-Aided Diagnosis for Lymph Nodes Using Unsupervised Domain-Adaptation Networks Based on Cross-Domain Confounding Representations.

Computational and mathematical methods in medicine Jan 24, 2020
To achieve the robust high-performance computer-aided diagnosis systems for lymph nodes, CT images may be typically collected from multicenter data, which cause the isolated performance of the model based on different data source centers. The variabi...
Humans Tomography, X-Ray Computed Diagnosis, Computer-Assisted Deep Learning Neural Networks, Computer Algorithms Unsupervised Machine Learning Radiographic Image Interpretation, Computer-Assisted Information Storage and Retrieval Computational Biology Lymph Nodes
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The implementation of natural language processing to extract index lesions from breast magnetic resonance imaging reports.

BMC medical informatics and decision making Dec 30, 2019
BACKGROUND: There are often multiple lesions in breast magnetic resonance imaging (MRI) reports and radiologists usually focus on describing the index lesion that is most crucial to clinicians in determining the management and prognosis of patients. ...
Breast Neoplasms Cross-Sectional Studies Magnetic Resonance Imaging Natural Language Processing Middle Aged Humans Female Breast Information Storage and Retrieval
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Selected articles from the BioCreative/OHNLP challenge 2018.

BMC medical informatics and decision making Dec 27, 2019
Natural Language Processing Information Storage and Retrieval Humans Electronic Health Records Computational Biology
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Family history information extraction via deep joint learning.

BMC medical informatics and decision making Dec 27, 2019
Family history (FH) information, including family members, side of family of family members (i.e., maternal or paternal), living status of family members, observations (diseases) of family members, etc., is very important in the decision-making proce...
Information Storage and Retrieval Medical History Taking Computational Biology Natural Language Processing Clinical Decision-Making Deep Learning Algorithms Electronic Health Records Humans
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Family member information extraction via neural sequence labeling models with different tag schemes.

BMC medical informatics and decision making Dec 27, 2019
BACKGROUND: Family history information (FHI) described in unstructured electronic health records (EHRs) is a valuable information source for patient care and scientific researches. Since FHI is usually described in the format of free text, the entire...
Information Storage and Retrieval Medical History Taking Electronic Health Records Natural Language Processing Neural Networks, Computer Algorithms Humans
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