AIMC Topic: Medical Oncology

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Adequacy and Effectiveness of Watson For Oncology in the Treatment of Thyroid Carcinoma.

Frontiers in endocrinology Mar 3, 2021
BACKGROUND: IBM's Watson for Oncology (WFO) is an artificial intelligence tool that trains by acquiring data from the Memorial Sloan Kettering Cancer Center and learns from test cases and experts. This study aimed to analyze the adequacy and effectiv...
Humans Neoplasm Staging Medical Oncology Practice Patterns, Physicians' Male Middle Aged Thyroid Neoplasms Decision Support Systems, Clinical Guideline Adherence Treatment Outcome Female Aged Adult Artificial Intelligence Retrospective Studies Republic of Korea
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Information retrieval on oncology knowledge base using recursive paraphrase lattice.

Journal of biomedical informatics Feb 11, 2021
For annotation in cancer genomic medicine, oncologists have to refer to various knowledge bases worldwide and retrieve all information (e.g., drugs, clinical trials, and academic papers) related to a gene variant. However, oncologists find it difficu...
Language Knowledge Bases Medical Oncology Information Storage and Retrieval
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Current cancer driver variant predictors learn to recognize driver genes instead of functional variants.

BMC biology Jan 13, 2021
BACKGROUND: Identifying variants that drive tumor progression (driver variants) and distinguishing these from variants that are a byproduct of the uncontrolled cell growth in cancer (passenger variants) is a crucial step for understanding tumorigenes...
Machine Learning Precision Medicine Neoplasms Disease Progression Carcinogenesis Medical Oncology
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Interactive Classification of Whole-Slide Imaging Data for Cancer Researchers.

Cancer research Dec 21, 2020
Whole-slide histology images contain information that is valuable for clinical and basic science investigations of cancer but extracting quantitative measurements from these images is challenging for researchers who are not image analysis specialists...
Biomedical Research Neoplasms Image Processing, Computer-Assisted Reproducibility of Results Sensitivity and Specificity Breast Neoplasms Image Interpretation, Computer-Assisted Medical Oncology Datasets as Topic Lymphocytes, Tumor-Infiltrating Predictive Value of Tests Melanoma, Cutaneous Malignant Software Algorithms Prognosis Female Melanoma Skin Neoplasms Humans Machine Learning
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Artificial intelligence in musculoskeletal oncological radiology.

Radiology and oncology Nov 10, 2020
BACKGROUND: Due to the rarity of primary bone tumors, precise radiologic diagnosis often requires an experienced musculoskeletal radiologist. In order to make the diagnosis more precise and to prevent the overlooking of potentially dangerous conditio...
Image Interpretation, Computer-Assisted Medical Oncology Humans Musculoskeletal Diseases Artificial Intelligence Diagnostic Imaging
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Academics as leaders in the cancer artificial intelligence revolution.

Cancer Oct 29, 2020
The successful translation of artificial intelligence (AI) applications into clinical cancer care practice requires guidance by academic cancer researchers and providers who are well poised to step into leadership roles. In this commentary, the autho...
Academies and Institutes Neoplasms Deep Learning Medical Oncology Algorithms Humans Leadership Artificial Intelligence
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Cancer Informatics in 2019: Deep Learning Takes Center Stage.

Yearbook of medical informatics Aug 21, 2020
OBJECTIVE: To summarize significant research contributions on cancer informatics published in 2019.
Medical Informatics Deep Learning Humans Radiography Lung Neoplasms Medical Oncology Neoplasms
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From Patient Engagement to Precision Oncology: Leveraging Informatics to Advance Cancer Care.

Yearbook of medical informatics Aug 21, 2020
OBJECTIVES: Conduct a survey of the literature for advancements in cancer informatics over the last three years in three specific areas where there has been unprecedented growth: 1) digital health; 2) machine learning; and 3) precision oncology. We a...
Medical Informatics Patient Participation Precision Medicine Neoplasms Medical Oncology Humans Machine Learning
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Artificial Intelligence and Mechanistic Modeling for Clinical Decision Making in Oncology.

Clinical pharmacology and therapeutics Aug 1, 2020
The amount of "big" data generated in clinical oncology, whether from molecular, imaging, pharmacological, or biological origin, brings novel challenges. To mine efficiently this source of information, mathematical models able to produce predictive a...
Models, Theoretical Humans Data Mining Artificial Intelligence Medical Oncology Decision Support Techniques Decision Support Systems, Clinical Clinical Decision-Making Electronic Health Records Genomics Neoplasms Immunotherapy Diagnosis, Computer-Assisted
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Artificial intelligence and radiomics in pediatric molecular imaging.

Methods (San Diego, Calif.) Jun 13, 2020
In the past decade, a new approach for quantitative analysis of medical images and prognostic modelling has emerged. Defined as the extraction and analysis of a large number of quantitative parameters from medical images, radiomics is an evolving fie...
Pediatrics Humans Medical Oncology Neural Networks, Computer Datasets as Topic Reproducibility of Results Patient Care Planning Prognosis Triage Child Telemedicine Image Processing, Computer-Assisted Molecular Imaging
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