Cardiovascular

A multiomics analysis-assisted deep learning model identifies a macrophage-oriented module as a potential therapeutic target in colorectal cancer.

Colorectal cancer (CRC) is a common malignancy involving multiple cellular components. The CRC tumor microenvironment (TME) has been characterized well at single-cell resolution. However, a spatial interaction map of the CRC TME is still elusive. Here, we integrate multiomics analyses and establish a spatial interaction map to improve the prognosis, prediction, and therapeutic development for CRC....

Deep learning-guided adjuvant chemotherapy selection for elderly patients with breast cancer.

PURPOSE: The efficacy of adjuvant chemotherapy in elderly breast cancer patients is currently controversial. This study aims to provide personalized adjuvant chemotherapy recommendations using deep learning (DL).

Edge roughness quantifies impact of physician variation on training and performance of deep learning auto-segmentation models for the esophagus.

Manual segmentation of tumors and organs-at-risk (OAR) in 3D imaging for radiation-therapy planning is time-consuming and subject to variation between...

ACPScanner: Prediction of Anticancer Peptides by Integrated Machine Learning Methodologies.

Novel therapeutic alternatives for cancer treatment are increasingly attracting global research attention. Although chemotherapy remains a primary cli...

Clinical assessment of deep learning-based uncertainty maps in lung cancer segmentation.

. Prior to radiation therapy planning, accurate delineation of gross tumour volume (GTVs) and organs at risk (OARs) is crucial. In the current clinica...

DARDN: A Deep-Learning Approach for CTCF Binding Sequence Classification and Oncogenic Regulatory Feature Discovery.

Characterization of gene regulatory mechanisms in cancer is a key task in cancer genomics. CCCTC-binding factor (CTCF), a DNA binding protein, exhibit...

Machine Learning Developed a MYC Expression Feature-Based Signature for Predicting Prognosis and Chemoresistance in Pancreatic Adenocarcinoma.

MYC has been identified to profoundly influence a wide range of pathologic processes in cancers. However, the prognostic value of MYC-related genes in...

Deep learning for computer-aided abnormalities classification in digital mammogram: A data-centric perspective.

Breast cancer is the most common type of cancer in women, and early abnormality detection using mammography can significantly improve breast cancer su...

Deep Learning Auto-Segmentation Network for Pediatric Computed Tomography Data Sets: Can We Extrapolate From Adults?

PURPOSE: Artificial intelligence (AI)-based auto-segmentation models hold promise for enhanced efficiency and consistency in organ contouring for adap...

CT image denoising methods for image quality improvement and radiation dose reduction.

With the ever-increasing use of computed tomography (CT), concerns about its radiation dose have become a significant public issue. To address the nee...

High-accuracy prediction of colorectal cancer chemotherapy efficacy using machine learning applied to gene expression data.

FOLFOX and FOLFIRI chemotherapy are considered standard first-line treatment options for colorectal cancer (CRC). However, the criteria for selecting...

A breast cancer-specific combinational QSAR model development using machine learning and deep learning approaches.

Breast cancer is the most prevalent and heterogeneous form of cancer affecting women worldwide. Various therapeutic strategies are in practice based o...

Artificial intelligence in biology and medicine, and radioprotection research: perspectives from Jerusalem.

While AI is widely used in biomedical research and medical practice, its use is constrained to few specific practical areas, e.g., radiomics. Particip...

The role of artificial intelligence in informed patient consent for radiotherapy treatments-a case report.

Recent advancements in large language models (LMM; e.g., ChatGPT (OpenAI, San Francisco, California, USA)) have seen widespread use in various fields,...

Prospective deployment of an automated implementation solution for artificial intelligence translation to clinical radiation oncology.

INTRODUCTION: Artificial intelligence (AI)-based technologies embody countless solutions in radiation oncology, yet translation of AI-assisted softwar...

Leveraging technology-driven strategies to untangle omics big data: circumventing roadblocks in clinical facets of oral cancer.

Oral cancer is one of the 19most rapidly progressing cancers associated with significant mortality, owing to its extreme degree of invasiveness and ag...

(mistletoe) extract for dogs with cancer?

Compared with the options available to human patients with cancer, treatment choices for dogs are often more limited. Chemotherapy is frequently the f...

Integrative analysis of RNA expression data unveils distinct cancer types through machine learning techniques.

Cancer is a highly complex and heterogeneous disease. Traditional methods of cancer classification based on histopathology have limitations in guiding...

AS-NeSt: A Novel 3D Deep Learning Model for Radiation Therapy Dose Distribution Prediction in Esophageal Cancer Treatment With Multiple Prescriptions.

PURPOSE: Implementing artificial intelligence technologies allows for the accurate prediction of radiation therapy dose distributions, enhancing treat...

Hydrogel spacer injection to the meso-sigmoid to protect the sigmoid colon in cervical cancer brachytherapy: A technical report.

PURPOSE: The use of a hydrogel spacer inserted into recto-vaginal fossa is a valuable strategy to mitigate radiation exposure to the rectum during rad...