Oncology/Hematology

Glioblastoma and Solitary Brain Metastasis: Differentiation by Integrating Demographic-MRI and Deep-Learning Radiomics Signatures.

BACKGROUND: Studies have shown that deep-learning radiomics (DLR) could help differentiate glioblast...

CT-Based Deep-Learning Model for Spread-Through-Air-Spaces Prediction in Ground Glass-Predominant Lung Adenocarcinoma.

BACKGROUND: Sublobar resection is strongly associated with poor prognosis in early-stage lung adenoc...

Deep learning catheter tip locations for photoacoustic-guided cardiac interventions.

SIGNIFICANCE: Interventional cardiac procedures often require ionizing radiation to guide cardiac ca...

Brain metastasis tumor segmentation and detection using deep learning algorithms: A systematic review and meta-analysis.

BACKGROUND: Manual detection of brain metastases is both laborious and inconsistent, driving the nee...

Robotic and laparoscopic sphincter-saving resections have similar peri-operative, oncological and functional outcomes in female patients with rectal cancer.

BACKGROUND: This study aimed to compare perioperative, long-term oncological, and anorectal function...

PROACTING: predicting pathological complete response to neoadjuvant chemotherapy in breast cancer from routine diagnostic histopathology biopsies with deep learning.

BACKGROUND: Invasive breast cancer patients are increasingly being treated with neoadjuvant chemothe...

Education by a social robot on nutrition and catheter care in pediatric oncology patients.

PURPOSE: To improve knowledge on nutrition and catheter care in children with cancer by an education...

Clinical service evaluation of the feasibility and reproducibility of novel artificial intelligence based-echocardiographic quantification of global longitudinal strain and left ventricular ejection fraction in trastuzumab-treated patients.

INTRODUCTION: Cardiotoxicity is a potential prognostically important complication of certain chemoth...

Unsupervised machine learning models reveal predictive clinical markers of glioblastoma patient survival using white blood cell counts prior to initiating chemoradiation.

BACKGROUND: Glioblastoma is a malignant brain tumor requiring careful clinical monitoring even after...

Editorial for "A Machine Learning-Based Unenhanced Radiomics Approach to Distinguishing Between Benign and Malignant Breast Lesions Using T2-Weighted and Diffusion-Weighted MRI".

Biochemical outcome after curative treatment for localized prostate cancer with external beam radiotherapy: a cross-sectional study.

Although many patients who receive definitive radiotherapy (RT) for localised prostate cancer (CaP) ...

Understanding the need for digital twins' data in patient advocacy and forecasting oncology.

Digital twins are made of a real-world component where data is measured and a virtual component wher...

Histological classification of canine and feline lymphoma using a modular approach based on deep learning and advanced image processing.

Histopathological examination of tissue samples is essential for identifying tumor malignancy and th...

Automated deep learning-based AMD detection and staging in real-world OCT datasets (PINNACLE study report 5).

Real-world retinal optical coherence tomography (OCT) scans are available in abundance in primary an...

Development of a hybrid hydrogel for submucosal injection in endoscopic resection of gastrointestinal neoplasm: From laboratory to clinical trial.

Submucosal injection solution is essential for successful endoscopic resection of the early gastroi...

An algorithm for drug discovery based on deep learning with an example of developing a drug for the treatment of lung cancer.

In this study, we present an algorithmic framework integrated within the created software platform t...

From cancer big data to treatment: Artificial intelligence in cancer research.

In recent years, developing the idea of "cancer big data" has emerged as a result of the significant...

A combined encoder-transformer-decoder network for volumetric segmentation of adrenal tumors.

BACKGROUND: The morphology of the adrenal tumor and the clinical statistics of the adrenal tumor are...

A Machine Learning-Based Unenhanced Radiomics Approach to Distinguishing Between Benign and Malignant Breast Lesions Using T2-Weighted and Diffusion-Weighted MRI.

BACKGROUND: Breast MRI has been recommended as supplemental screening tool to mammography and breast...

Predictive value and potential association of PET/CT radiomics on lymph node metastasis of cervical cancer.

OBJECTIVE: Due to the information-rich nature of positron emission tomography/computed tomography (P...

A Preliminary Investigation into Search and Matching for Tumor Discrimination in World Health Organization Breast Taxonomy Using Deep Networks.

Breast cancer is one of the most common cancers affecting women worldwide. It includes a group of ma...