AIMC Topic: Leukemia, Lymphocytic, Chronic, B-Cell
Clear Filters Showing 11 to 20 of 27 articles
Dynamic Bayesian networks for prediction of health status and treatment effect in patients with chronic lymphocytic leukemia.
Scientific reports
Feb 2, 2022
Chronic lymphocytic leukemia (CLL) is the most common blood cancer in adults. The course of CLL and patients' response to treatment are varied. This variability makes it difficult to select the most appropriate treatment regimen and predict the progr...
Humans
Artificial Intelligence
Health Status
Predictive Value of Tests
Decision Support Techniques
Risk Assessment
Bayes Theorem
Aged
Clinical Decision-Making
Disease Progression
Health Status Indicators
Female
Leukemia, Lymphocytic, Chronic, B-Cell
Time Factors
Risk Factors
Male
Treatment Outcome
Middle Aged
Artificial intelligence strategy integrating morphologic and architectural biomarkers provides robust diagnostic accuracy for disease progression in chronic lymphocytic leukemia.
The Journal of pathology
Oct 25, 2021
Artificial intelligence-based tools designed to assist in the diagnosis of lymphoid neoplasms remain limited. The development of such tools can add value as a diagnostic aid in the evaluation of tissue samples involved by lymphoma. A common diagnosti...
Artificial intelligence models in chronic lymphocytic leukemia - recommendations toward state-of-the-art.
Leukemia & lymphoma
Oct 6, 2021
Artificial intelligence (AI), machine learning and predictive modeling are becoming enabling technologies in many day-to-day applications. Translation of these advances to the patient's bedside for AI assisted interventions is not yet the norm. With ...
IoMT-Based Automated Detection and Classification of Leukemia Using Deep Learning.
Journal of healthcare engineering
Dec 3, 2020
For the last few years, computer-aided diagnosis (CAD) has been increasing rapidly. Numerous machine learning algorithms have been developed to identify different diseases, e.g., leukemia. Leukemia is a white blood cells- (WBC-) related illness affec...
Leukemia, Myeloid, Acute
Diagnosis, Computer-Assisted
COVID-19
Telemedicine
Deep Learning
Algorithms
Humans
Cloud Computing
Diagnostic Imaging
Databases, Factual
Neural Networks, Computer
Internet of Things
Leukemia, Myelogenous, Chronic, BCR-ABL Positive
Machine Learning
Leukemia, Lymphocytic, Chronic, B-Cell
Pattern Recognition, Automated
Leukemia
Precursor Cell Lymphoblastic Leukemia-Lymphoma
Hematologist-Level Classification of Mature B-Cell Neoplasm Using Deep Learning on Multiparameter Flow Cytometry Data.
Cytometry. Part A : the journal of the International Society for Analytical Cytology
Jun 9, 2020
The wealth of information captured by multiparameter flow cytometry (MFC) can be analyzed by recent methods of computer vision when represented as a single image file. We therefore transformed MFC raw data into a multicolor 2D image by a self-organiz...
Machine learning can identify newly diagnosed patients with CLL at high risk of infection.
Nature communications
Jan 17, 2020
Infections have become the major cause of morbidity and mortality among patients with chronic lymphocytic leukemia (CLL) due to immune dysfunction and cytotoxic CLL treatment. Yet, predictive models for infection are missing. In this work, we develop...
Machine learning applications in the diagnosis of leukemia: Current trends and future directions.
International journal of laboratory hematology
Sep 9, 2019
Machine learning (ML) offers opportunities to advance pathological diagnosis, especially with increasing trends in digitalizing microscopic images. Diagnosing leukemia is time-consuming and challenging in many areas globally and there is a growing tr...
Automatic data source identification for clinical trial eligibility criteria resolution.
AMIA ... Annual Symposium proceedings. AMIA Symposium
Feb 10, 2017
Clinical trial coordinators refer to both structured and unstructured sources of data when evaluating a subject for eligibility. While some eligibility criteria can be resolved using structured data, some require manual review of clinical notes. An i...
Design of Biomedical Robots for Phenotype Prediction Problems.
Journal of computational biology : a journal of computational molecular cell biology
Jun 27, 2016
Genomics has been used with varying degrees of success in the context of drug discovery and in defining mechanisms of action for diseases like cancer and neurodegenerative and rare diseases in the quest for orphan drugs. To improve its utility, accur...
Protein Profiles Predict Treatment Responses to the PI3K Inhibitor Umbralisib in Patients with Chronic Lymphocytic Leukemia.
Clinical cancer research : an official journal of the American Association for Cancer Research
May 15, 2025
PURPOSE: The management of chronic lymphocytic leukemia (CLL) has significantly improved with targeted therapies. However, many patients experience a suboptimal response. To optimally select the best therapy, predictive biomarkers are necessary. In t...
Biomarkers, Tumor
Leukemia, Lymphocytic, Chronic, B-Cell
Male
Middle Aged
Humans
Female
Aged
Aged, 80 and over
Protein Kinase Inhibitors
Antineoplastic Combined Chemotherapy Protocols
Agammaglobulinaemia Tyrosine Kinase
Treatment Outcome
Benzamides
Pyrazines
Phosphoinositide-3 Kinase Inhibitors
Phosphatidylinositol 3-Kinases
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