AIMC Topic: Blood Cell Count

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Developing an Improved Statistical Approach for Survival Estimation in Bone Metastases Management: The Bone Metastases Ensemble Trees for Survival (BMETS) Model.

International journal of radiation oncology, biology, physics May 22, 2020
PURPOSE: To determine whether a machine learning approach optimizes survival estimation for patients with symptomatic bone metastases (SBM), we developed the Bone Metastases Ensemble Trees for Survival (BMETS) to predict survival using 27 prognostic ...
Male Middle Aged Steroids Time Factors Pelvic Bones Algorithms Prognosis Female Reproducibility of Results Spinal Neoplasms Proportional Hazards Models Kaplan-Meier Estimate Life Expectancy Karnofsky Performance Status Bone Neoplasms Area Under Curve Analgesics, Opioid Palliative Care Blood Cell Count Humans Machine Learning
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SDCT-AuxNet: DCT augmented stain deconvolutional CNN with auxiliary classifier for cancer diagnosis.

Medical image analysis Feb 4, 2020
Acute lymphoblastic leukemia (ALL) is a pervasive pediatric white blood cell cancer across the globe. With the popularity of convolutional neural networks (CNNs), computer-aided diagnosis of cancer has attracted considerable attention. Such tools are...
Humans Neural Networks, Computer Diagnosis, Computer-Assisted Deep Learning Datasets as Topic Blood Cell Count Precursor Cell Lymphoblastic Leukemia-Lymphoma
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Regular cold water swimming during winter time affects resting hematological parameters and serum erythropoietin.

Journal of physiology and pharmacology : an official journal of the Polish Physiological Society Jan 30, 2020
Recreational winter swimming in cold sea water evokes body responses to regularly repeated cold water immersion. However, the understanding of adaptive changes is still limited and data regarding very short-term exposure to severe cold stress are sca...
Erythropoietin Water Blood Platelets Humans Erythrocytes Female Cold Temperature Hemoglobins Rest Male Folic Acid Seasons Middle Aged Blood Cell Count Swimming Hematocrit Immunoglobulins
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Diagnosis and classification of pediatric acute appendicitis by artificial intelligence methods: An investigator-independent approach.

PloS one Sep 25, 2019
Acute appendicitis is one of the major causes for emergency surgery in childhood and adolescence. Appendectomy is still the therapy of choice, but conservative strategies are increasingly being studied for uncomplicated inflammation. Diagnosis of acu...
Adolescent Child, Preschool Child Ultrasonography ROC Curve Infant, Newborn Male Infant Diagnosis, Computer-Assisted Appendix C-Reactive Protein Appendicitis Germany Blood Cell Count Appendectomy Humans Artificial Intelligence Machine Learning Algorithms Biomarkers Retrospective Studies Female
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Blood Biochemistry Analysis to Detect Smoking Status and Quantify Accelerated Aging in Smokers.

Scientific reports Jan 15, 2019
There is an association between smoking and cancer, cardiovascular disease and all-cause mortality. However, currently, there are no affordable and informative tests for assessing the effects of smoking on the rate of biological aging. In this study ...
Humans Artificial Intelligence Risk Factors Middle Aged Sex Factors Deep Learning Blood Chemical Analysis Aging, Premature Blood Cell Count Age Factors Smoking Supervised Machine Learning Smokers
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Prediction of findings at screening colonoscopy using a machine learning algorithm based on complete blood counts (ColonFlag).

PloS one Nov 27, 2018
Adenomatous polyps are a common precursor lesion for colorectal cancer. ColonFlag is a machine- learning-based algorithm that uses basic patient information and complete blood cell counts (CBC) to identify individuals at elevated risk of colorectal c...
Mass Screening Blood Cell Count Aged Colorectal Neoplasms Male Middle Aged Colonoscopy Humans Machine Learning Female
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Early Colorectal Cancer Detected by Machine Learning Model Using Gender, Age, and Complete Blood Count Data.

Digestive diseases and sciences Aug 23, 2017
BACKGROUND: Machine learning tools identify patients with blood counts indicating greater likelihood of colorectal cancer and warranting colonoscopy referral.
Humans Machine Learning Odds Ratio Algorithms Female Reproducibility of Results ROC Curve Age Factors Early Detection of Cancer Predictive Value of Tests Colorectal Neoplasms Registries Area Under Curve Male Data Mining Risk Factors Middle Aged Sex Factors Aged Colonoscopy Referral and Consultation Aged, 80 and over Diagnosis, Computer-Assisted Blood Cell Count Adult
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Correlations of Complete Blood Count with Alanine and Aspartate Transaminase in Chinese Subjects and Prediction Based on Back-Propagation Artificial Neural Network (BP-ANN).

Medical science monitor : international medical journal of experimental and clinical research Jun 19, 2017
BACKGROUND The complete blood count (CBC) is the most common examination used to monitor overall health in clinical practice. Whether there is a relationship between CBC indexes and alanine transaminase (ALT) and aspartate aminotransferase (AST) has ...
Asian People Alanine Transaminase Aspartate Aminotransferases Blood Cell Count Female Adult Male Overweight Regression Analysis Humans Neural Networks, Computer
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Machine Learning Based Single-Frame Super-Resolution Processing for Lensless Blood Cell Counting.

Sensors (Basel, Switzerland) Nov 2, 2016
A lensless blood cell counting system integrating microfluidic channel and a complementary metal oxide semiconductor (CMOS) image sensor is a promising technique to miniaturize the conventional optical lens based imaging system for point-of-care test...
Blood Cell Count Microfluidic Analytical Techniques Humans Machine Learning Flow Cytometry Semiconductors
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Evaluation of supervised machine-learning algorithms to distinguish between inflammatory bowel disease and alimentary lymphoma in cats.

Journal of veterinary diagnostic investigation : official publication of the American Association of Veterinary Laboratory Diagnosticians, Inc Oct 3, 2016
Inflammatory bowel disease (IBD) and alimentary lymphoma (ALA) are common gastrointestinal diseases in cats. The very similar clinical signs and histopathologic features of these diseases make the distinction between them diagnostically challenging. ...
Animals Diagnostic Techniques and Procedures Blood Chemical Analysis Male Neural Networks, Computer Blood Cell Count Machine Learning Lymphoma Cats Algorithms Decision Trees Cat Diseases Inflammatory Bowel Diseases Bayes Theorem Female
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