Leukemia

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 crucial step in establishing diagnosis of acute leukemia, especially in low-resource settings where other diagnostic modalities are not available, the task remains time-consuming and prone to human inconsistencies. This has an impact especially in cases of Acute Promyelocytic Leukemia (APL) that req...

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 treatment from a theoretical point of view. A mathematical model describing the dynamics of tumor growth under the drug interventions of chemotherapy and antiangiogenic therapy is considered. The model incorporates the effects of normal cells, cancer cells, and endothelial cells. Then, the control g...

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 states is an important topic in medicine and is valuab...

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 tissue is important to many areas of musculoskeletal ...

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 undergo additional testing to exclude acute coron...

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 conventional manual operation is time-consuming and l...

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 predict pathological complete response (PCR), residual ...

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 chemotherapy followed by resection. Chemotherapy ...

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 function. Multiple genes collectively control cel...

Molecular modeling of C1-inhibitor as SARS-CoV-2 target identified from the immune signatures of multiple tissues: An integrated bioinformatics study.

The expeditious transmission of the severe acute respiratory coronavirus 2 (SARS-CoV-2), a strain of COVID-19, crumbled the global economic strength a...

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 platinum salt and polyADP-ribose polymerase inhibitor che...

Deep-learning-based personalized prediction of absolute neutrophil count recovery and comparison with clinicians for validation.

Neutropenia and its complications are major adverse effects of cytotoxic chemotherapy. The time to recovery from neutropenia varies from patient to pa...

An Enhanced Hyper-Parameter Optimization of a Convolutional Neural Network Model for Leukemia Cancer Diagnosis in a Smart Healthcare System.

Healthcare systems in recent times have witnessed timely diagnoses with a high level of accuracy. Internet of Medical Things (IoMT)-enabled deep learn...

Stature estimation by semi-automatic measurements of 3D CT images of the femur.

Stature estimation is one of the most basic and important methods of personal identification. The long bones of the limbs provide the most accurate st...

Hybrid Intelligence-Driven Medical Image Recognition for Remote Patient Diagnosis in Internet of Medical Things.

In ear of smart cities, intelligent medical image recognition technique has become a promising way to solve remote patient diagnosis in IoMT. Although...

Impact of Warm Ischemia on Acute Kidney Injury After Robotic Partial Nephrectomy Stratified by Baseline Kidney Function.

To evaluate the differences in baseline chronic kidney disease (CKD) status in correlations between warm ischemic time (WIT) and acute kidney injury ...

Epidemiological Features of Acute Myeloid Leukemia in Five Regions of the Republic of Kazakhstan: Population Study.

OBJECTIVE: The aim of the study was to assess the main epidemiological characteristics of AML (morbidity, survival, distribution by AML variants and a...

AlphaFill: enriching AlphaFold models with ligands and cofactors.

Artificial intelligence-based protein structure prediction approaches have had a transformative effect on biomolecular sciences. The predicted protein...

An integrated deep learning model for the prediction of pathological complete response to neoadjuvant chemotherapy with serial ultrasonography in breast cancer patients: a multicentre, retrospective study.

BACKGROUND: The biological phenotype of tumours evolves during neoadjuvant chemotherapy (NAC). Accurate prediction of pathological complete response (...

Deep learning radiomics of ultrasonography for comprehensively predicting tumor and axillary lymph node status after neoadjuvant chemotherapy in breast cancer patients: A multicenter study.

BACKGROUND: Neoadjuvant chemotherapy (NAC) can downstage tumors and axillary lymph nodes in breast cancer (BC) patients. However, tumors and axillary ...