Oncology/Hematology

Breast Cancer

Latest AI and machine learning research in breast cancer for healthcare professionals.

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CNN-based deep learning approach for classification of invasive ductal and metastasis types of breast carcinoma.

OBJECTIVE: Breast cancer is one of the leading cancer causes among women worldwide. It can be classi...

Predicting tumor mutation burden and VHL mutation from renal cancer pathology slides with self-supervised deep learning.

BACKGROUND: Tumor mutation burden (TMB) and VHL mutation play a crucial role in the management of pa...

EDRAM-Net: Encoder-Decoder with Residual Attention Module Network for Low-dose Computed Tomography Reconstruction.

The medical application of Computed Tomography (CT) is to provide detailed anatomical structures of ...

Rapid assessment of cosmic radiation exposure in aviation based on BP neural network method.

Cosmic radiation exposure is one of the important health concerns for aircrews. In this work, we con...

Performance evaluation of ML models for preoperative prediction of HER2-low BC based on CE-CBBCT radiomic features: A prospective study.

To explore the value of machine learning (ML) models based on contrast-enhanced cone-beam breast com...

Validating linalool as a potential drug for breast cancer treatment based on machine learning and molecular docking.

Breast cancer (BC) is a common cancer for women. This study aims to construct a prognostic risk mode...

Familiarity, confidence and preference of artificial intelligence feedback and prompts by Australian breast cancer screening readers.

Objectives This study explored the familiarity, perceptions and confidence of Australian radiology c...

Use of Deep Learning to Evaluate Tumor Microenvironmental Features for Prediction of Colon Cancer Recurrence.

UNLABELLED: Deep learning may detect biologically important signals embedded in tumor morphologic fe...

Patient Characteristics Impact Performance of AI Algorithm in Interpreting Negative Screening Digital Breast Tomosynthesis Studies.

Background Artificial intelligence (AI) is increasingly used to manage radiologists' workloads. The ...

PBAC: A pathway-based attention convolution neural network for predicting clinical drug treatment responses.

Precise and personalized drug application is crucial in the clinical treatment of complex diseases. ...

Artificial intelligence-powered optimization of KI-67 assessment in breast cancer: enhancing precision and workflow efficiency. a literature review.

Breast Cancer (BC) has evolved from traditional morphological analysis to molecular profiling, ident...

Using Machine Learning to Predict Unplanned Hospital Utilization and Chemotherapy Management From Patient-Reported Outcome Measures.

PURPOSE: Adverse effects of chemotherapy often require hospital admissions or treatment management. ...

Advanced Technologies in Radiation Research.

The U.S. Government is committed to maintaining a robust research program that supports a portfolio ...

Robot-assisted laparoscopic surgery for rectal cancer in a patient with a horseshoe kidney: A case report.

A 52-year-old, Japanese man presented to the hospital with a complaint of anal bleeding, and detaile...

Eravacycline, an antibacterial drug, repurposed for pancreatic cancer therapy: insights from a molecular-based deep learning model.

BACKGROUND: Pancreatic ductal adenocarcinoma (PDAC) remains a serious threat to health, with limited...

Improving drug response prediction via integrating gene relationships with deep learning.

Predicting the drug response of cancer cell lines is crucial for advancing personalized cancer treat...

[Current status and prospects for the application of robot-assisted spine surgery].

Traditional spine surgery frequently encounters difficulties with inadequate surgical visualization ...

Safety and Feasibility of Single-Port Robotic-Assisted Nipple-Sparing Mastectomy.

IMPORTANCE: Robotic-assisted nipple-sparing mastectomies with multiport robots have been described i...

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