Oncology/Hematology

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

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The development of an artificial intelligence auto-segmentation tool for 3D volumetric analysis of vestibular schwannomas.

Linear and volumetric analysis are the typical methods to measure tumor size. 3D volumetric analysis...

Towards full integration of explainable artificial intelligence in colon capsule endoscopy's pathway.

Despite recent surge of interest in deploying colon capsule endoscopy (CCE) for early diagnosis of c...

Linear regressive weighted Gaussian kernel liquid neural network for brain tumor disease prediction using time series data.

A brain tumor is an abnormal growth of cells within the brain or surrounding tissues, which can be e...

Integration of 101 machine learning algorithm combinations to unveil m6A/m1A/m5C/m7G-associated prognostic signature in colorectal cancer.

Colorectal cancer (CRC) is the most common malignancy in the digestive system, with a lower 5-year o...

Long-term solar radiation forecasting in India using EMD, EEMD, and advanced machine learning algorithms.

Solar radiation plays a critical role in the carbon sequestration processes of terrestrial ecosystem...

Assessment of AI-based computational H&E staining versus chemical H&E staining for primary diagnosis in lymphomas: a brief interim report.

Microscopic review of tissue sections is of foundational importance in pathology, yet the traditiona...

Leveraging natural language processing for efficient information extraction from breast cancer pathology reports: Single-institution study.

BACKGROUND: Pathology reports provide important information for accurate diagnosis of cancer and opt...

Multimodal deep learning: tumor and visceral fat impact on colorectal cancer occult peritoneal metastasis.

OBJECTIVES: This study proposes a multimodal deep learning (DL) approach to investigate the impact o...

Comparative performance of PD-L1 scoring by pathologists and AI algorithms.

AIM: This study evaluates the comparative effectiveness of pathologists versus artificial intelligen...

Artificial Intelligence for Drug Discovery: An Update and Future Prospects.

Artificial intelligence (AI) has become a pivotal tool for medical image analysis, significantly enh...

FusionNet: Dual input feature fusion network with ensemble based filter feature selection for enhanced brain tumor classification.

Brain tumors pose a significant threat to human health, require a precise and quick diagnosis for ef...

Radiation oncology at crossroads: Rise of AI and managing the unexpected.

Integrating artificial intelligence (AI) into radiation oncology has revolutionized clinical workflo...

A series of natural language processing for predicting tumor response evaluation and survival curve from electronic health records.

BACKGROUND: The clinical information housed within unstructured electronic health records (EHRs) has...

Comparative analysis of intestinal tumor segmentation in PET CT scans using organ based and whole body deep learning.

BACKGROUND: 18-Fluoro-deoxyglucose positron emission tomography/computed tomography (FDG-PET/CT) is ...

A predictive model for recurrence in patients with borderline ovarian tumor based on neural multi-task logistic regression.

BACKGROUND: Effective management of patients with borderline ovarian tumor (BOT) requires the timely...

Realizing the promise of machine learning in precision oncology: expert perspectives on opportunities and challenges.

BACKGROUND: The ability of machine learning (ML) to process and learn from large quantities of heter...

Diagnosis of Benign and Malignant Newly Developed Nodules on the Surgical Side After Breast Cancer Surgery Based on Machine Learning.

To enhance the diagnostic accuracy of new nodules on the surgical side after breast cancer surgery ...

Prior knowledge-based multi-task learning network for pulmonary nodule classification.

The morphological characteristics of pulmonary nodule, also known as the attributes, are crucial for...

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