Oncology/Hematology

Integrating different data types by regularized unsupervised multiple kernel learning with application to cancer subtype discovery.

MOTIVATION: Despite ongoing cancer research, available therapies are still limited in quantity and effectiveness, and making treatment decisions for individual patients remains a hard problem. Established subtypes, which help guide these decisions, are mainly based on individual data types. However, the analysis of multidimensional patient data involving the measurements of various molecular featu...

Validating FMEA output against incident learning data: A study in stereotactic body radiation therapy.

PURPOSE: Though failure mode and effects analysis (FMEA) is becoming more widely adopted for risk assessment in radiation therapy, to our knowledge, its output has never been validated against data on errors that actually occur. The objective of this study was to perform FMEA of a stereotactic body radiation therapy (SBRT) treatment planning process and validate the results against data recorded w...

[Study on Sleep Staging Based on Support Vector Machines and Feature Selection in Single Channel Electroencephalogram].

Sleep electroencephalogram (EEG) is an important index in diagnosing sleep disorders and related diseases. Manual sleep staging is time-consuming and ...

[Automatic Sleep Staging Method Based on Energy Features and Least Squares Support Vector Machine Classifier].

The research of sleep staging is not only the basis of diagnosing sleep related diseases, but also the precondition of evaluating sleep quality, and h...

Risk Factors Associated with Intraoperative Major Blood Loss during Resection of Hepatocellular Carcinoma.

BACKGROUND/AIMS: Intraoperative blood loss is an independent predictor of recurrence and survival after resection of hepatocellular carcinoma (HCC). T...

Simultaneous Laparoscopic Resection of Primary Tumor and Liver Metastases for Colorectal Cancer: Surgical Technique and Short-Term Outcome.

BACKGROUND/AIMS: Laparoscopic approaches are increasingly used in selected patients with either colorectal or liver disease. The aim of this study was...

New Prognostic Indicator is Useful for Predicting the Survival of Patients with Unresectable Advanced Colorectal Cancer.

BACKGROUND/AIMS: Complete resection of tumors is possible after heavy chemotherapy in a few patients with unresectable colorectal cancer (UCRC). This ...

The combination of artificial neural networks and synchrotron radiation-based infrared micro-spectroscopy for a study on the protein composition of human glial tumors.

Protein-related changes associated with the development of human brain gliomas are of increasing interest in modern neuro-oncology. It is due to the f...

Models for predicting objective function weights in prostate cancer IMRT.

PURPOSE: To develop and evaluate the clinical applicability of advanced machine learning models that simultaneously predict multiple optimization obje...

Automatic learning-based beam angle selection for thoracic IMRT.

PURPOSE: The treatment of thoracic cancer using external beam radiation requires an optimal selection of the radiation beam directions to ensure effec...

Down syndrome and leukemia: insights into leukemogenesis and translational targets.

Children with Down syndrome (DS) have a significantly increased risk of childhood leukemia, in particular acute megakaryoblastic leukemia (AMKL) and a...

Prechemotherapy robotic-assisted laparoscopic radical nephrectomy for an adolescent with Wilms tumor.

Although Wilms tumor (WT) is the most common pediatric renal tumor, adolescent and adult WT is rare. Nevertheless, adolescent renal tumors as a group ...

Comparison between target margins derived from 4DCT scans and real-time tumor motion tracking: insights from lung tumor patients treated with robotic radiosurgery.

PURPOSE: A unique capability of the CyberKnife system is dynamic target tracking. However, not all patients are eligible for this approach. Rather, th...

[Robot-assisted laparoscopic partial nephrectomy: functional and oncological outcomes].

BACKGROUND: In recent years, small renal masses (SRM) have been increasingly detected as an incidental finding of radiological or ultrasound studies f...

Laparoscopic hysterectomy with a handheld robotic device in a case of uterine sarcoma.

Practice innovation: the need for nimble data platforms to implement precision oncology care.

Given the drive toward personalized, value-based, and coordinated cancer care delivery, modern knowledge-based practice is being shaped within the con...

Adaptive Fuzzy Consensus Clustering Framework for Clustering Analysis of Cancer Data.

Performing clustering analysis is one of the important research topics in cancer discovery using gene expression profiles, which is crucial in facilit...

Design, architecture and application of nanorobotics in oncology.

Oncologists all over the globe, relentlessly research on methodologies for detection of cancer and precise localization of cancer therapeutics with mi...

Long-term oncologic outcomes of robotic low anterior resection for rectal cancer: a comparative study with laparoscopic surgery.

OBJECTIVE: The aim of this study is to evaluate long-term oncologic outcomes of robotic surgery for rectal cancer compared with laparoscopic surgery a...

Identification of hepatocellular carcinoma-related genes with a machine learning and network analysis.

Liver cancer is one of the leading causes of cancer mortality worldwide. Hepatocellular carcinoma (HCC) is the main type of liver cancer. We applied a...