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Artificial Intelligence and Machine Learning in Pathology: The Present Landscape of Supervised Methods

Academic Pathology, 2019, Vol.6, p.2374289519873088-2374289519873088, Article 2374289519873088

2019

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Synthetic Data and Its Utility in Pathology and Laboratory Medicine

Laboratory investigation, 2024-08, Vol.104 (8), p.102095, Article 102095

2024

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Novel application of automated machine learning with MALDI-TOF-MS for rapid high-throughput screening of COVID-19: a proof of concept

Scientific reports, 2021-04, Vol.11 (1), p.8219-8219, Article 8219

2021

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Comparative performance of two automated machine learning platforms for COVID-19 detection by MALDI-TOF-MS

PloS one, 2022-07, Vol.17 (7), p.e0263954

2022

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A novel and fully automated platform for synthetic tabular data generation and validation

Scientific reports, 2024-10, Vol.14 (1), p.23312-11, Article 23312

2024

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Preface: Artificial intelligence (AI), machine learning ML) and digital pathology integration are the next major chapter in our diagnostic pathology and laboratory medicine arena

Seminars in diagnostic pathology, 2023-03, Vol.40 (2), p.69-70

2023

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Venous thromboembolism in the era of machine learning and artificial intelligence in medicine

Thrombosis research, 2024-10, Vol.242, p.109121, Article 109121

2024

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Immune response dynamics in COVID-19 patients to SARS-CoV-2 and other human coronaviruses

PloS one, 2021-07, Vol.16 (7), p.e0254367-e0254367

2021

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Machine learning in the coagulation and hemostasis arena: an overview and evaluation of methods, review of literature, and future directions

Journal of thrombosis and haemostasis, 2023-04, Vol.21 (4), p.728-743

2023

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Machine learning in health care and laboratory medicine: General overview of supervised learning and Auto‐ML

International journal of laboratory hematology, 2021-07, Vol.43 (S1), p.15-22

2021

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Artificial intelligence and machine learning overview in pathology & laboratory medicine: A general review of data preprocessing and basic supervised concepts

Seminars in diagnostic pathology, 2023-03, Vol.40 (2), p.71-87

2023

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Machine learning and artificial intelligence for the diagnosis of infectious diseases in immunocompromised patients

Current opinion in infectious diseases, 2023-08, Vol.36 (4), p.235

2023

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Early Recognition of Burn- and Trauma-Related Acute Kidney Injury: A Pilot Comparison of Machine Learning Techniques

Scientific reports, 2020-01, Vol.10 (1), p.205-205, Article 205

2020

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Artificial intelligence and machine learning for predicting acute kidney injury in severely burned patients: A proof of concept

Burns, 2019-09, Vol.45 (6), p.1350-1358

2019

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Regulatory Aspects of Artificial Intelligence and Machine Learning

Modern pathology, 2024-12, Vol.37 (12), p.100609, Article 100609

2024

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Common statistical concepts in the supervised Machine Learning arena

Frontiers in oncology, 2023-02, Vol.13, p.1130229-1130229

2023

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Automated En Masse Machine Learning Model Generation Shows Comparable Performance as Classic Regression Models for Predicting Delayed Graft Function in Renal Allografts

Transplantation, 2021-12, Vol.105 (12), p.2646-2654

2021

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Automated machine learning for endemic active tuberculosis prediction from multiplex serological data

Scientific reports, 2021-09, Vol.11 (1), p.17900-17900, Article 17900

2021

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Individual and community factors contributing to anemia among women in rural Baja California, Mexico

PloS one, 2017-11, Vol.12 (11), p.e0188590-e0188590

2017

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Comparing machine learning screening approaches using clinical data and cytokine profiles for COVID-19 in resource-limited and resource-abundant settings

Scientific reports, 2024-06, Vol.14 (1), p.14892-9, Article 14892

2024

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Novel application of an automated-machine learning development tool for predicting burn sepsis: proof of concept

Scientific reports, 2020-07, Vol.10 (1), p.12354-12354, Article 12354

2020

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Generative AI in orthopedics: an explainable deep few-shot image augmentation pipeline for plain knee radiographs and Kellgren-Lawrence grading

Journal of the American Medical Informatics Association : JAMIA, 2024-11, Vol.31 (11), p.2668-2678

2024

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Elevated periprostatic venous testosterone correlates with prostate cancer progression after radical prostatectomy

The Journal of clinical investigation, 2023-09, Vol.133 (17), p.1-8

2023

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Importance of bone marrow clot sections—Positive for metastatic tumor

International journal of laboratory hematology, 2022-08, Vol.44 (4), p.696-697

2022

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Analyzing Anatomic Pathology On-Call Summaries to Improve Resident Education

Archives of pathology & laboratory medicine (1976), 2022-01, Vol.146 (1), p.112-116

2022

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Artificial Intelligence and Machine Learning in Pathology: The Present Landscape of Supervised Methods

Synthetic Data and Its Utility in Pathology and Laboratory Medicine

Novel application of automated machine learning with MALDI-TOF-MS for rapid high-throughput screening of COVID-19: a proof of concept

Comparative performance of two automated machine learning platforms for COVID-19 detection by MALDI-TOF-MS

A novel and fully automated platform for synthetic tabular data generation and validation

Preface: Artificial intelligence (AI), machine learning ML) and digital pathology integration are the next major chapter in our diagnostic pathology and laboratory medicine arena

Venous thromboembolism in the era of machine learning and artificial intelligence in medicine

Immune response dynamics in COVID-19 patients to SARS-CoV-2 and other human coronaviruses

Machine learning in the coagulation and hemostasis arena: an overview and evaluation of methods, review of literature, and future directions

Machine learning in health care and laboratory medicine: General overview of supervised learning and Auto‐ML

Artificial intelligence and machine learning overview in pathology & laboratory medicine: A general review of data preprocessing and basic supervised concepts

Machine learning and artificial intelligence for the diagnosis of infectious diseases in immunocompromised patients

Early Recognition of Burn- and Trauma-Related Acute Kidney Injury: A Pilot Comparison of Machine Learning Techniques

Artificial intelligence and machine learning for predicting acute kidney injury in severely burned patients: A proof of concept

Regulatory Aspects of Artificial Intelligence and Machine Learning

Common statistical concepts in the supervised Machine Learning arena

Automated En Masse Machine Learning Model Generation Shows Comparable Performance as Classic Regression Models for Predicting Delayed Graft Function in Renal Allografts

Automated machine learning for endemic active tuberculosis prediction from multiplex serological data

Individual and community factors contributing to anemia among women in rural Baja California, Mexico

Comparing machine learning screening approaches using clinical data and cytokine profiles for COVID-19 in resource-limited and resource-abundant settings

Novel application of an automated-machine learning development tool for predicting burn sepsis: proof of concept

Generative AI in orthopedics: an explainable deep few-shot image augmentation pipeline for plain knee radiographs and Kellgren-Lawrence grading

Elevated periprostatic venous testosterone correlates with prostate cancer progression after radical prostatectomy

Importance of bone marrow clot sections—Positive for metastatic tumor

Analyzing Anatomic Pathology On-Call Summaries to Improve Resident Education

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