Oncology/Hematology

Pectoralis muscle predicts distant metastases in breast cancer by deep learning radiomics.

BACKGROUND: Sarcopenia is associated with a poor prognosis in patients with breast cancer (BC). Currently, there are few quantitative assessments carried out between muscle biomarkers and distant metastasis using existing methods.

Short-term outcomes of robot-assisted versus video-assisted thoracoscopic surgery for non-small cell lung cancer patients with neoadjuvant immunochemotherapy: a single-center retrospective study.

BACKGROUND: Neoadjuvant immunochemotherapy has been increasingly applied to treat non-small cell lung cancer (NSCLC). However, the comparison between robotic-assisted thoracoscopic surgery (RATS) and video-assisted thoracoscopic surgery (VATS) in the feasibility and oncological efficacy following neoadjuvant immunochemotherapy is scarce. This study aims to assess the superiorities of RATS over (VA...

Modeling Epidemiology Data with Machine Learning Technique to Detect Risk Factors for Gastric Cancer.

PURPOSE: Gastric cancer (GC) ranks as the 7th most common cancer worldwide and a leading cause of cancer mortality. In Iran, stomach malignancies are ...

Deep learning model for predicting the survival of patients with primary gastrointestinal lymphoma based on the SEER database and a multicentre external validation cohort.

PURPOSE: Due to the rarity of primary gastrointestinal lymphoma (PGIL), the prognostic factors and optimal management of PGIL have not been clearly de...

A patient-specific deep learning framework for 3D motion estimation and volumetric imaging during lung cancer radiotherapy.

. Respiration introduces a constant source of irregular motion that poses a significant challenge for the precise irradiation of thoracic and abdomina...

Preoperative Prediction of Microvascular Invasion with Gadoxetic Acid-Enhanced Magnetic Resonance Imaging in Patients with Single Hepatocellular Carcinoma: The Implication of Surgical Decision on the Extent of Liver Resection.

INTRODUCTION: Microvascular invasion (MVI) is one of the most important prognostic factors for hepatocellular carcinoma (HCC) recurrence, but its appl...

Complete mesocolic excision versus standard resection for colon cancer: a systematic review and meta-analysis of perioperative safety and an evaluation of the use of a robotic approach.

PURPOSE: Complete mesocolic excision (CME) has been associated with improved oncological outcomes in treatment of colon cancer. However, widespread ad...

Machine learning to predict environmental dose rates from a radionuclide therapy service - a proof of concept study.

The Ionising Radiation Regulations 2017 requires prior risk assessment calculations and regular environmental monitoring of radiation doses. However, ...

Editorial for "Deep Learning Nomogram for the Identification of Deep Stromal Invasion in Patients With Early-Stage Cervical Adenocarcinoma and Adenosquamous Carcinoma: A Multicenter Study".

Harnessing the power of artificial intelligence to advance cell therapy.

Cell therapies are powerful technologies in which human cells are reprogrammed for therapeutic applications such as killing cancer cells or replacing ...

A hierarchical self-attention-guided deep learning framework to predict breast cancer response to chemotherapy using pre-treatment tumor biopsies.

BACKGROUND: Pathological complete response (pCR) to neoadjuvant chemotherapy (NAC) has demonstrated a strong correlation to improved survival in breas...

Propensity matched analysis of robotic and laparoscopic operations for mid-low rectal cancer: short-term comparison of anal function and oncological outcomes.

Laparoscopic surgery for rectal cancer, while in some respects equivalent or even preferable to open surgery, is challenged in specific conditions whe...

Pearls and pitfalls of ChatGPT in medical oncology.

Recently, ChatGPT has drawn attention to the potential uses of artificial intelligence (AI) in academia. Here, we discuss how ChatGPT can be of value ...

Cancer immunotherapy response prediction from multi-modal clinical and image data using semi-supervised deep learning.

BACKGROUND AND PURPOSE: Immunotherapy is a standard treatment for many tumor types. However, only a small proportion of patients derive clinical benef...

Deep-learning image reconstruction for 80-kVp pancreatic CT protocol: Comparison of image quality and pancreatic ductal adenocarcinoma visibility with hybrid-iterative reconstruction.

PURPOSE: To evaluate the image quality and visibility of pancreatic ductal adenocarcinoma (PDAC) in 80-kVp pancreatic CT protocol and compare them bet...

Deep Learning Nomogram for the Identification of Deep Stromal Invasion in Patients With Early-Stage Cervical Adenocarcinoma and Adenosquamous Carcinoma: A Multicenter Study.

BACKGROUND: Deep stromal invasion (DSI) is one of the predominant risk factors that determined the types of radical hysterectomy (RH). Thus, the accur...

Deep learning-assisted LI-RADS grading and distinguishing hepatocellular carcinoma (HCC) from non-HCC based on multiphase CT: a two-center study.

OBJECTIVES: To develop a deep learning (DL) method that can determine the Liver Imaging Reporting and Data System (LI-RADS) grading of high-risk liver...

Deep learning applications in single-cell genomics and transcriptomics data analysis.

Traditional bulk sequencing methods are limited to measuring the average signal in a group of cells, potentially masking heterogeneity, and rare popul...

The prediction of drug sensitivity by multi-omics fusion reveals the heterogeneity of drug response in pan-cancer.

Cancer drug response prediction based on genomic information plays a crucial role in modern pharmacogenomics, enabling individualized therapy. Given t...

Deep learning radio-clinical signatures for predicting neoadjuvant chemotherapy response and prognosis from pretreatment CT images of locally advanced gastric cancer patients.

BACKGROUND: Early noninvasive screening of patients who would benefit from neoadjuvant chemotherapy (NCT) is essential for personalized treatment of l...