Oncology/Hematology

Latest AI and machine learning research in oncology/hematology for healthcare professionals.

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Unrolled deep learning for breast cancer detection using limited-view photoacoustic tomography data.

Photoacoustic tomography (PAT) has emerged as a promising imaging modality for breast cancer detecti...

NAVT-net neuron attention visual taylor network for lung cancer detection using CT images.

Lung Cancer is regarded as a common fatal disease affecting humans throughout the entire world. Earl...

Single-cell RNA sequencing and machine learning provide candidate drugs against drug-tolerant persister cells in colorectal cancer.

Drug resistance often stems from drug-tolerant persister (DTP) cells in cancer. These cells arise fr...

OCDet: A comprehensive ovarian cell detection model with channel attention on immunohistochemical and morphological pathology images.

BACKGROUND: Ovarian cancer is among the most lethal gynecologic malignancy that threatens women's li...

An automatic cervical cell classification model based on improved DenseNet121.

The cervical cell classification technique can determine the degree of cellular abnormality and path...

A quantum-optimized approach for breast cancer detection using SqueezeNet-SVM.

Breast cancer is one of the most aggressive types of cancer, and its early diagnosis is crucial for ...

Colorectal cancer detection with enhanced precision using a hybrid supervised and unsupervised learning approach.

The current work introduces the hybrid ensemble framework for the detection and segmentation of colo...

Intestinal Microbiome Modulation of Therapeutic Efficacy of Cancer Immunotherapy.

Bacteria are associated with certain cancers and may induce genetic instability and cancer progressi...

Enhanced brain tumor detection and segmentation using densely connected convolutional networks with stacking ensemble learning.

- Brain tumors (BT), both benign and malignant, pose a substantial impact on human health and need p...

Detecting B-cell lymphoma-6 overexpression status in primary central nervous system lymphoma using multiparametric MRI-based machine learning.

PURPOSE: In primary central nervous system lymphoma (PCNSL), B-cell lymphoma-6 (BCL-6) is an unfavor...

Ultrasensitive Detection of Circulating Plasma Cells Using Surface-Enhanced Raman Spectroscopy and Machine Learning for Multiple Myeloma Monitoring.

Multiple myeloma is a hematologic malignancy characterized by the proliferation of abnormal plasma c...

Multiomic machine learning on lactylation for molecular typing and prognosis of lung adenocarcinoma.

To integrate machine learning and multiomic data on lactylation-related genes (LRGs) for molecular t...

Immunolipid magnetic bead-based circulating tumor cell sorting: a novel approach for pathological staging of colorectal cancer.

OBJECTIVE: This study aimed to assess whether circulating tumor cells (CTCs) from colorectal cancer ...

Non-parametric Bayesian deep learning approach for whole-body low-dose PET reconstruction and uncertainty assessment.

Positron emission tomography (PET) imaging plays a pivotal role in oncology for the early detection ...

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