Oncology/Hematology

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

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Showing 4033-4053 of 15,377 articles
Establishment of a prognostic model for gastric cancer patients who underwent radical gastrectomy using machine learning: a two-center study.

OBJECTIVE: Gastric cancer is a prevalent gastrointestinal malignancy worldwide. In this study, a pro...

LensePro: label noise-tolerant prototype-based network for improving cancer detection in prostate ultrasound with limited annotations.

PURPOSE: The standard of care for prostate cancer (PCa) diagnosis is the histopathological analysis ...

Advancing predictive markers in lung adenocarcinoma: A machine learning-based immunotherapy prognostic prediction signature.

The prognosis of lung adenocarcinoma (LUAD) is generally poor. Immunotherapy has emerged as a promis...

Deep learning-based compressed SENSE improved diffusion-weighted image quality and liver cancer detection: A prospective study.

PURPOSE: To assess whether diffusion-weighted imaging (DWI) with Compressed SENSE (CS) and deep lear...

Deep causal learning for pancreatic cancer segmentation in CT sequences.

Segmenting the irregular pancreas and inconspicuous tumor simultaneously is an essential but challen...

Clinical evaluation of deep learning-based risk profiling in breast cancer histopathology and comparison to an established multigene assay.

PURPOSE: To evaluate the Stratipath Breast tool for image-based risk profiling and compare it with a...

S2DA-Net: Spatial and spectral-learning double-branch aggregation network for liver tumor segmentation in CT images.

Accurate liver tumor segmentation is crucial for aiding radiologists in hepatocellular carcinoma eva...

Conversion to Radical Nephrectomy From Robotic Partial Nephrectomy Is Most Commonly Due to Anatomic and Oncologic Complexity.

PURPOSE: Partial nephrectomy is standard-of-care treatment for small renal masses. As utilization of...

Applying Machine Learning for Enhanced MicroRNA Analysis: A Companion Risk Tool for Oral Squamous Cell Carcinoma in Standard Care Incisional Biopsy.

Machine learning analyses within the realm of oral cancer outcomes are relatively underexplored comp...

Development and validation of an ultrasound-based deep learning radiomics nomogram for predicting the malignant risk of ovarian tumours.

BACKGROUND: The timely identification and management of ovarian cancer are critical determinants of ...

Deep learning assists in acute leukemia detection and cell classification via flow cytometry using the acute leukemia orientation tube.

This study aimed to evaluate the sensitivity of AI in screening acute leukemia and its capability to...

An Automated Deep Learning-Based Framework for Uptake Segmentation and Classification on PSMA PET/CT Imaging of Patients with Prostate Cancer.

Uptake segmentation and classification on PSMA PET/CT are important for automating whole-body tumor ...

Diagnostic performance of a deep-learning model using F-FDG PET/CT for evaluating recurrence after radiation therapy in patients with lung cancer.

OBJECTIVE: We developed a deep learning model for distinguishing radiation therapy (RT)-related chan...

Harnessing artificial intelligence for prostate cancer management.

Prostate cancer (PCa) is a common malignancy in males. The pathology review of PCa is crucial for cl...

Boosting Clear Cell Renal Carcinoma-Specific Drug Discovery Using a Deep Learning Algorithm and Single-Cell Analysis.

Clear cell renal carcinoma (ccRCC), the most common subtype of renal cell carcinoma, has the high he...

Lung Cancer Diagnosis on Virtual Histologically Stained Tissue Using Weakly Supervised Learning.

Lung adenocarcinoma (LUAD) is the most common primary lung cancer and accounts for 40% of all lung c...

Is Risk-Stratifying Patients with Colorectal Cancer Using a Deep Learning-Based Prognostic Biomarker Cost-Effective?

OBJECTIVES: Accurate risk stratification of patients with stage II and III colorectal cancer (CRC) p...

A muti-modal feature fusion method based on deep learning for predicting immunotherapy response.

Immune checkpoint therapy (ICT) has greatly improved the survival of cancer patients in the past few...

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