Oncology/Hematology

Deep learning-based dominant index lesion segmentation for MR-guided radiation therapy of prostate cancer.

BACKGROUND: Dose escalation radiotherapy enables increased control of prostate cancer (PCa) but requires segmentation of dominant index lesions (DIL). This motivates the development of automated methods for fast, accurate, and consistent segmentation of PCa DIL.

Perioperative, functional, and oncologic outcomes of robot-assisted versus open partial nephrectomy for complex renal tumors (RENAL score ≥ 7): an evidence-based analysis.

This study aims to assess the efficacy and safety of robot-assisted partial nephrectomy (RAPN) compared with open partial nephrectomy (OPN) in the management of complex renal tumors (defined as RENAL score ≥ 7). We conducted a comprehensive literature search in PubMed, Embase, Web of Science, and Cochrane Library to identify relevant comparative studies up to January 2023. This study was conducted...

Equivalent radiation exposure with robotic total hip replacement using a novel, fluoroscopic-guided (CT-free) system: case-control study versus manual technique.

Accurate and precise positioning of the acetabular cup remains a prevalent challenge in total hip arthroplasty (THA). Robotic assistance for THA has i...

A machine learning based approach for quantitative evaluation of cell migration in Transwell assays based on deformation characteristics.

Many pathological and physiological processes, including embryonic development, immune response and cancer metastasis, involve studies on cell migrati...

Beyond diagnosis: is there a role for radiomics in prostate cancer management?

The role of imaging in pretreatment staging and management of prostate cancer (PCa) is constantly evolving. In the last decade, there has been an ever...

Prediction of lymph node metastasis in stage T1-2 rectal cancers with MRI-based deep learning.

OBJECTIVES: This study aimed to investigate whether a deep learning (DL) model based on preoperative MR images of primary tumors can predict lymph nod...

Unpaired low-dose computed tomography image denoising using a progressive cyclical convolutional neural network.

BACKGROUND: Reducing the radiation dose from computed tomography (CT) can significantly reduce the radiation risk to patients. However, low-dose CT (L...

Clinical application of AI-based PET images in oncological patients.

Based on the advantages of revealing the functional status and molecular expression of tumor cells, positron emission tomography (PET) imaging has bee...

From patterns to patients: Advances in clinical machine learning for cancer diagnosis, prognosis, and treatment.

Machine learning (ML) is increasingly used in clinical oncology to diagnose cancers, predict patient outcomes, and inform treatment planning. Here, we...

Deep Learning Prediction of Promoter Mutation Status in Thyroid Cancer Using Histologic Images.

objectives: Telomerase reverse transcriptase () promoter mutation, found in a subset of patients with thyroid cancer, is strongly associated with agg...

MEMMAL: A tool for expanding large-scale mechanistic models with machine learned associations and big datasets.

Computational models that can explain and predict complex sub-cellular, cellular, and tissue-level drug response mechanisms could speed drug discovery...

Comparison between robot-assisted versus open nephroureterectomy for upper tract urothelial carcinoma: outcomes from a pooled analysis.

The present study aimed to compare the efficacy and safety between robot-assisted nephroureterectomy (RANU) and open nephroureterectomy (ONU) for the ...

A Novel IoT-Enabled Healthcare Monitoring Framework and Improved Grey Wolf Optimization Algorithm-Based Deep Convolution Neural Network Model for Early Diagnosis of Lung Cancer.

Lung cancer is a high-risk disease that causes mortality worldwide; nevertheless, lung nodules are the main manifestation that can help to diagnose lu...

Detection of malignancy in whole slide images of endometrial cancer biopsies using artificial intelligence.

In this study we use artificial intelligence (AI) to categorise endometrial biopsy whole slide images (WSI) from digital pathology as either "malignan...

Clinicians' perception of oral potentially malignant disorders: a pitfall for image annotation in supervised learning.

OBJECTIVE: The present study aims to quantify clinicians' perceptions of oral potentially malignant disorders (OPMDs) when evaluating, classifying, an...

Successful all robotic-assisted excision of highly malignant mediastinal neuroblastoma in a toddler: A case report.

An otherwise well 28-month-old girl presented with fever/left thigh pain. Computed tomography identified a 7 cm right posterior mediastinal tumor exte...

Evaluation of deep learning based implanted fiducial markers tracking in pancreatic cancer patients.

Real-time target position verification during pancreas stereotactic body radiation therapy (SBRT) is important for the detection of unplanned tumour m...

Comparison of Perioperative Outcomes and Complications of Laparoscopic and Robotic Nephroureterectomy Approaches in Patients with Upper-Tract Urothelial Carcinoma.

BACKGROUND: For medical institutions without robotic equipment, it remains uncertain whether laparoscopic radical nephroureterectomy (LNU) can achieve...

Automated Ki-67 labeling index assessment in prostate cancer using artificial intelligence and multiplex fluorescence immunohistochemistry.

The Ki-67 labeling index (Ki-67 LI) is a strong prognostic marker in prostate cancer, although its analysis requires cumbersome manual quantification ...

Artificial intelligence-based model for lymph node metastases detection on whole slide images in bladder cancer: a retrospective, multicentre, diagnostic study.

BACKGROUND: Accurate lymph node staging is important for the diagnosis and treatment of patients with bladder cancer. We aimed to develop a lymph node...