Oncology/Hematology

[Preliminary application of transoral robotic thyroidectomy: experience from an initial 30 cases].

To examine the surgical outcome of transoral robotic thyroidectomy. Clinic data of total 30 cases of transoral robotic thyroidectomy at the Department of Thyroid and Breast Surgery, the 960 Hospital of People's Liberation Army from May 2020 to December 2020 were analyzed retrospectively. There were 3 males and 27 females, aged (31.5±11.0) years (range: 17 to 55 years), including 6 cases of benig...

Applications of Artificial Intelligence in Pediatric Oncology: A Systematic Review.

PURPOSE: There is a need for an improved understanding of clinical and biologic risk factors in pediatric cancer to improve patient outcomes. Machine learning (ML) represents the application of computational inference from advanced statistical methods that can be applied to increasing amount of data available for study in pediatric oncology. The goal of this systematic review was to systematically...

[A place of robot-assisted cystectomy in treatment of muscle-invasive bladder cancer].

Bladder cancer occupies one of the leading positions in morbidity in the world and constitutes a serious problem for healthcare system. The muscle-inv...

[Robot Assisted Lower Anterior Resection for Anastomotic Recurrence of Colorectal Cancer-A Case Report].

Patient undergoing R0 resection have the good survival advantage following surgery for recurrent rectal cancer. Robotic surgery for anastomotic local ...

Applications of artificial intelligence in radiophysics.

Artificial intelligence (AI) is playing an important role in radiation oncology. One of the most important applications is in radiotherapy physics. In...

Efficacy and safety of carboplatin with nab-paclitaxel versus docetaxel in older patients with squamous non-small-cell lung cancer (CAPITAL): a randomised, multicentre, open-label, phase 3 trial.

BACKGROUND: In Japan, docetaxel, a cytotoxic monotherapy, is the standard drug administered to older patients with advanced non-small-cell lung cancer...

Use of machine learning to transform complex standardized nursing care plan data into meaningful research variables: a palliative care exemplar.

The aim of this article was to describe a novel methodology for transforming complex nursing care plan data into meaningful variables to assess the im...

Machine learning integrates genomic signatures for subclassification beyond primary and secondary acute myeloid leukemia.

Although genomic alterations drive the pathogenesis of acute myeloid leukemia (AML), traditional classifications are largely based on morphology, and ...

De Novo Identification and Visualization of Important Cell Populations for Classic Hodgkin Lymphoma Using Flow Cytometry and Machine Learning.

OBJECTIVES: Automated classification of flow cytometry data has the potential to reduce errors and accelerate flow cytometry interpretation. We desire...

Prediction of tumor purity from gene expression data using machine learning.

MOTIVATION: Bulk tumor samples used for high-throughput molecular profiling are often an admixture of cancer cells and non-cancerous cells, which incl...

Knowledge bases and software support for variant interpretation in precision oncology.

Precision oncology is a rapidly evolving interdisciplinary medical specialty. Comprehensive cancer panels are becoming increasingly available at patho...

Integration and interplay of machine learning and bioinformatics approach to identify genetic interaction related to ovarian cancer chemoresistance.

Although chemotherapy is the first-line treatment for ovarian cancer (OCa) patients, chemoresistance (CR) decreases their progression-free survival. T...

OCTID: a one-class learning-based Python package for tumor image detection.

MOTIVATION: Tumor tile selection is a necessary prerequisite in patch-based cancer whole slide image analysis, which is labor-intensive and requires e...

The accurate prediction and characterization of cancerlectin by a combined machine learning and GO analysis.

Cancerlectins, lectins linked to tumor progression, have become the focus of cancer therapy research for their carbohydrate-binding specificity. Howev...

DISMIR: Deep learning-based noninvasive cancer detection by integrating DNA sequence and methylation information of individual cell-free DNA reads.

Detecting cancer signals in cell-free DNA (cfDNA) high-throughput sequencing data is emerging as a novel noninvasive cancer detection method. Due to t...

Artificial intelligence and machine learning methods in predicting anti-cancer drug combination effects.

Drug combinations have exhibited promising therapeutic effects in treating cancer patients with less toxicity and adverse side effects. However, it is...

Drug sensitivity prediction from cell line-based pharmacogenomics data: guidelines for developing machine learning models.

The goal of precision oncology is to tailor treatment for patients individually using the genomic profile of their tumors. Pharmacogenomics datasets s...

Fully Automated Gross Tumor Volume Delineation From PET in Head and Neck Cancer Using Deep Learning Algorithms.

PURPOSE: The availability of automated, accurate, and robust gross tumor volume (GTV) segmentation algorithms is critical for the management of head a...

Feasibility and Accuracy of Artificial Intelligence-Assisted Sponge Cytology for Community-Based Esophageal Squamous Cell Carcinoma Screening in China.

INTRODUCTION: Screening is the pivotal strategy to relieve the burden of esophageal squamous cell carcinoma (ESCC) in high-risk areas. The cost, invas...

The quantification and clinical analysis of depression and anxiety in patients undergoing Da Vinci robot-assisted radical gastrectomy and open radical gastrectomy.

The purpose of paper is to investigate the depression and anxiety as well as independent influential factors between patients who underwent Da Vinci r...