Oncology/Hematology

A collaborative workflow between pathologists and deep learning for the evaluation of tumour cellularity in lung adenocarcinoma.

AIMS: The reporting of tumour cellularity in cancer samples has become a mandatory task for patholog...

Artificial intelligence for oral cancer diagnosis: What are the possibilities?

Oral cancer could be prevented. The primary strategy is based on prevention. Most patients with oral...

DACBT: deep learning approach for classification of brain tumors using MRI data in IoT healthcare environment.

The classification of brain tumors (BT) is significantly essential for the diagnosis of Brian cancer...

RCMNet: A deep learning model assists CAR-T therapy for leukemia.

Acute leukemia is a type of blood cancer with a high mortality rate. Current therapeutic methods inc...

Region Convolutional Neural Network for Brain Tumor Segmentation.

Gliomas are often difficult to find and distinguish using typical manual segmentation approaches bec...

DeepMTS: Deep Multi-Task Learning for Survival Prediction in Patients With Advanced Nasopharyngeal Carcinoma Using Pretreatment PET/CT.

Nasopharyngeal Carcinoma (NPC) is a malignant epithelial cancer arising from the nasopharynx. Surviv...

Identifying Drug Targets of Oral Squamous Cell Carcinoma through a Systems Biology Method and Genome-Wide Microarray Data for Drug Discovery by Deep Learning and Drug Design Specifications.

In this study, we provide a systems biology method to investigate the carcinogenic mechanism of oral...

A Study on the Prediction of Cancer Using Whole-Genome Data and Deep Learning.

The number of patients diagnosed with cancer continues to increasingly rise, and has nearly doubled ...

Prediction of lipomatous soft tissue malignancy on MRI: comparison between machine learning applied to radiomics and deep learning.

OBJECTIVES: Malignancy of lipomatous soft-tissue tumours diagnosis is suspected on magnetic resonanc...

Differentiating single cervical cells by mitochondrial fluorescence imaging and deep learning-based label-free light scattering with multi-modal static cytometry.

Cervical cancer is a high-risk disease that threatens women's health globally. In this study, we dev...

Non-small cell lung cancer diagnosis aid with histopathological images using Explainable Deep Learning techniques.

BACKGROUND: Lung cancer has the highest mortality rate in the world, twice as high as the second hig...

Machine learning applications in gynecological cancer: A critical review.

Machine Learning (ML) represents a computer science capable of generating predictive models, by expo...

Editorial Comment to Robot-assisted laparoscopic versus open partial nephrectomy for renal cell carcinoma in patients with severe chronic kidney disease.

Advances in mass spectrometry imaging for spatial cancer metabolomics.

Mass spectrometry (MS) has become a central technique in cancer research. The ability to analyze var...

Diagnostic Assessment of Deep Learning Algorithms for Frozen Tissue Section Analysis in Women with Breast Cancer.

PURPOSE: Assessing the metastasis status of the sentinel lymph nodes (SLNs) for hematoxylin and eosi...

A novel multimodal deep learning model for preoperative prediction of microvascular invasion and outcome in hepatocellular carcinoma.

BACKGROUND: Accurate preoperative identification of the microvascular invasion (MVI) can relieve the...

Photon-counting Detector CT with Deep Learning Noise Reduction to Detect Multiple Myeloma.

Background Photon-counting detector (PCD) CT and deep learning noise reduction may improve spatial r...

An Edge-Based Selection Method for Improving Regions-of-Interest Localizations Obtained Using Multiple Deep Learning Object-Detection Models in Breast Ultrasound Images.

Computer-aided diagnosis (CAD) systems can be used to process breast ultrasound (BUS) images with th...

Comparing machine learning algorithms to predict 5-year survival in patients with chronic myeloid leukemia.

INTRODUCTION: Chronic myeloid leukemia (CML) is a myeloproliferative disorder resulting from the tra...

Global research trends and foci of artificial intelligence-based tumor pathology: a scientometric study.

BACKGROUND: With the development of digital pathology and the renewal of deep learning algorithm, ar...

Deep learning-based breast cancer grading and survival analysis on whole-slide histopathology images.

Breast cancer tumor grade is strongly associated with patient survival. In current clinical practice...