Oncology/Hematology

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 hepat...

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...

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 envi...

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 appli...

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 ...

Pearls and pitfalls of ChatGPT in medical oncology.

Recently, ChatGPT has drawn attention to the potential uses of artificial intelligence (AI) in acade...

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...

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 ...

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 ...

Surgery of the alimentary tract for benign and malignant disease with the novel robotic platform HUGO RAS. A first world report of safety and feasibility.

INTRODUCTION: As robotic surgery increases its reach, novel platforms are being released. We present...

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 t...

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 an...

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 pharmaco...

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,...

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 ...

Evaluation of breast tumor morphologies from African American and Caucasian patients.

The primary aim of this research was to investigate potential differences of breast tumor morphologi...

A CT-based deep learning radiomics nomogram outperforms the existing prognostic models for outcome prediction in clear cell renal cell carcinoma: a multicenter study.

OBJECTIVES: To develop and validate a CT-based deep learning radiomics nomogram (DLRN) for outcome p...

Deep learning-based combination of [18F]-FDG PET and CT images for producing pulmonary perfusion image.

BACKGROUND: The main application of [18F] FDG-PET ( FDG-PET) and CT images in oncology is tumor iden...

Deep learning based automated delineation of the intraprostatic gross tumour volume in PSMA-PET for patients with primary prostate cancer.

PURPOSE: With the increased use of focal radiation dose escalation for primary prostate cancer (PCa)...

Prediction of IDO1 Inhibitors by a Fingerprint-Based Stacking Ensemble Model Named IDO1Stack.

Indoleamine 2,3-dioxygenase 1 (IDO1) is viewed as an extremely promising target for cancer immunothe...