Hematology

Leukemia

Latest AI and machine learning research in leukemia for healthcare professionals.

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Automated quantification of measurable residual disease in chronic lymphocytic leukemia using an artificial intelligence-assisted workflow.

Detection of measurable residual disease (MRD) in chronic lymphocytic leukemia (CLL) is an important...

Strategy toward Kinase-Selective Drug Discovery.

Kinase drug selectivity is the ground challenge in cancer research. Due to the structurally similar ...

Non-destructive classification of unlabeled cells: Combining an automated benchtop magnetic resonance scanner and artificial intelligence.

In order to treat degenerative diseases, the importance of advanced therapy medicinal products has i...

Detection of acute promyelocytic leukemia in peripheral blood and bone marrow with annotation-free deep learning.

While optical microscopy inspection of blood films and bone marrow aspirates by a hematologist is a ...

Adaptive fuzzy control of drug delivery in cancer treatment using combination of chemotherapy and antiangiogenic therapy.

This paper introduces the adaptive fuzzy control scheme as a promising control technique for cancer ...

Deep learning model integrating positron emission tomography and clinical data for prognosis prediction in non-small cell lung cancer patients.

BACKGROUND: Lung cancer is the leading cause of cancer-related deaths worldwide. The majority of lun...

Development and validation of questionnaire-based machine learning models for predicting all-cause mortality in a representative population of China.

BACKGROUND: Considering that the previously developed mortality prediction models have limited appli...

Auto-segmentation of the tibia and femur from knee MR images via deep learning and its application to cartilage strain and recovery.

The ability to efficiently and reproducibly generate subject-specific 3D models of bone and soft tis...

High precision tracking analysis of cell position and motion fields using 3D U-net network models.

Cells are the basic units of biological organization, and the quantitative analysis of cellular stat...

Using Transfer Learning of Convolutional Neural Network on Neck Radiographs to Identify Acute Epiglottitis.

Acute epiglottitis (AE) is a life-threatening condition and needs to be recognized timely. Diagnosis...

Deep Learning Analysis of Chest Radiographs to Triage Patients with Acute Chest Pain Syndrome.

Background Patients presenting to the emergency department (ED) with acute chest pain (ACP) syndrome...

An AI-Aided Diagnostic Framework for Hematologic Neoplasms Based on Morphologic Features and Medical Expertise.

A morphologic examination is essential for the diagnosis of hematological diseases. However, its con...

Deep learning prediction of pathological complete response, residual cancer burden, and progression-free survival in breast cancer patients.

The goal of this study was to employ novel deep-learning convolutional-neural-network (CNN) to predi...

Deep Learning-Based Objective and Reproducible Osteosarcoma Chemotherapy Response Assessment and Outcome Prediction.

Osteosarcoma is the most common primary bone cancer, whose standard treatment includes pre-operative...

Ensemble learning based assessment of the role of transcription factors in gene expression.

Cancer cells are formed when the associated, active genes fail to function the way they are meant to...

Comparing different robots available in the European market for the preparation of injectable chemotherapy and recommendations to users.

INTRODUCTION: Recent advances in technology have made it possible to develop robots for preparing in...

Deep learning identifies morphological patterns of homologous recombination deficiency in luminal breast cancers from whole slide images.

Homologous recombination DNA-repair deficiency (HRD) is becoming a well-recognized marker of platinu...

NetBCE: An Interpretable Deep Neural Network for Accurate Prediction of Linear B-cell Epitopes.

Identification of B-cell epitopes (BCEs) plays an essential role in the development of peptide vacci...

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