Leukemia

Histopathologic deep learning model for predicting tumor response to hepatic arterial infusion chemotherapy plus TKIs and ICIs in large hepatocellular carcinoma.

BACKGROUND: While triplet therapy (HTI), which combines hepatic arterial infusion chemotherapy (HAIC) with tyrosine kinase inhibitors and immune checkpoint inhibitors, is widely used in the treatment of large hepatocellular carcinoma (HCC), there are few reports about its efficacy versus HAIC, and no reliable methods are available for promptly predicting HTI response.

A Novel Boundary-Aware Transformer Based Fire Hawk Algorithm for Leukemia Classification using Blood Smear Images.

Leukemia is a type of blood cancer affecting people of all ages and is the leading cause of death worldwide. The most common form of bone marrow leukemia is acute lymphoblastic leukemia (ALL). Diagnoses often require highly invasive diagnostic procedures, which are expensive and time-consuming. To overcome these issues, a novel Boundary-Aware Transformer based Fire Hawk Algorithm (BAT-FIRE) model ...

Predicting therapeutic clinical trial enrollment for adult patients with low- and high-grade glioma using supervised machine learning.

Therapeutic clinical trial enrollment does not match glioma incidence across demographics. Traditional statistical methods have identified independent...

Development of a machine learning-based model to predict urethral recurrence following radical cystectomy: a multicentre retrospective study and updated meta-analysis.

Urethral recurrence (UR) following radical cystectomy for bladder cancer represents an aggressive disease failure with typically poor survival outcome...

Advancing blood cell detection and classification: performance evaluation of modern deep learning models.

The detection and classification of blood cells are important in diagnosing and monitoring a variety of blood-related illnesses, such as anemia, leuke...

From Molecular Precision to Clinical Practice: A Comprehensive Review of Bispecific and Trispecific Antibodies in Hematologic Malignancies.

Multispecific antibodies have redefined the immunotherapeutic landscape in hematologic malignancies. Bispecific antibodies (BsAbs), which redirect cyt...

Development of an immune scoring system based on exosome-related gene expression for prognosis and treatment response prediction in breast cancer.

Breast cancer (BC) is a heterogeneous disease with diverse subtypes that influence prognosis and treatment outcomes. While advances have been made in ...

Neddylation status determines the therapeutic sensitivity of tyrosine kinase inhibitors in chronic myeloid leukemia.

BCR::ABL1-targeting tyrosine kinase inhibitors (TKIs) dominate the treatment of chronic myeloid leukemia (CML) over the past decades. In this study, w...

Gaussian random fields as an abstract representation of patient metadata for multimodal medical image segmentation.

Growing rates of chronic wound occurrence, especially in patients with diabetes, has become a recent concerning trend. Chronic wounds are difficult an...

The analgesic mechanism of electroacupuncture at the central level for neuropathic pain: a review of studies based on animal experiments.

This article analyzes the progress of animal experiments on the analgesic mechanism of electroacupuncture (EA) at the central level for neuropathic pa...

Gasdermin D drives the systemic storm and mortality after trauma with hemorrhage to a greater degree in biological females than males.

Severe injury accompanied by hemorrhagic shock triggers an early release of cell constituents into the circulation, referred to as the systemic storm....

Computed Tomography-Based Radiomics Diagnostic Model for Fat-Poor Small Renal Tumor Subtypes.

Differentiating histologic subtypes of fat-poor small renal masses using conventional imaging remains difficult due to their overlapping radiologic c...

Error Reduction in Leukemia Machine Learning Classification With Conformal Prediction.

PURPOSE: Recent advances in machine learning have led to the development of classifiers that predict molecular subtypes of acute lymphoblastic leukemi...

Corrigendum: Identification of hub genes and immune-related pathways in acute myeloid leukemia: insights from bioinformatics and experimental validation.

[This corrects the article DOI: 10.3389/fimmu.2024.1511824.].

Autophagy crosstalk with the immune microenvironment in chronic myeloid leukemia and serves as a biomarker for diagnosis and progression.

BACKGROUND: Previous studies have shown that autophagy is closely related to the occurrence, development, and treatment resistance of chronic myeloid ...

Identification of a novel chemotherapy benefit index for patients with advanced ovarian cancer based on Bayesian network analysis.

BACKGROUND: This study aims to evaluate the efficacy of chemotherapy and optimize treatment strategies for patients with advanced ovarian cancer.

Novel machine learning models for the prediction of acute respiratory distress syndrome after liver transplantation.

Early prediction of acute respiratory distress syndrome (ARDS) after liver transplantation (LT) facilitates timely intervention. We aimed to develop a...

Drug repurposing to identify potential FDA-approved drugs targeting three main angiogenesis receptors through a deep learning framework.

Tumor cell survival depends on the presence of oxygen and nutrients provided by existing blood vessels, particularly when cancer is in its early stage...

A novel fractional computational neural framework for analyzing cancer model under chemotherapy drug.

In this study, a novel Caputo fractional-order model is proposed to represent the complex interactions among stem cells, effector cells, and tumor cel...

In-silico evaluation of Azadirachta indica-derived Daucosterol against key viral proteins of Ebolavirus using ML and MD simulations approach.

Ebola virus disease (EVD) is an acute life-threatening disease caused by highly pathogenic Ebolavirus (EBOV), with reported case fatality rates reachi...