Oncology/Hematology

Robot-assisted laparoscopic surgery combined with axitinib for renal cell carcinoma and inferior vena cava tumor thrombi in a patient with severe obesity and obstructive sleep apnea-hypopnea syndrome: A case report.

Will It Play in Peoria? A Pilot Study of a Robotic Skills Curriculum for Surgical Oncology Fellows.

INTRODUCTION: To implement a mastery-based robotic surgery curriculum using virtual reality (VR) and inanimate reality (IR) drills at multiple Complex General Surgical Oncology (CGSO) fellowships.

Automated system for diagnosing endometrial cancer by adopting deep-learning technology in hysteroscopy.

Endometrial cancer is a ubiquitous gynecological disease with increasing global incidence. Therefore, despite the lack of an established screening tec...

Simulating reference crop evapotranspiration with different climate data inputs using Gaussian exponential model.

Obtaining accurate data on reference crop evapotranspiration (ET) is important for agricultural water management. A novel Gaussian exponential model (...

Development and Validation of a Radiomics Model for Differentiating Bone Islands and Osteoblastic Bone Metastases at Abdominal CT.

Background It is important to diagnose sclerotic bone lesions in order to determine treatment strategy. Purpose To evaluate the diagnostic performance...

Single-stage Xi® robotic radical nephroureterectomy for upper tract urothelial carcinoma: surgical technique and outcomes.

BACKGROUND: Radical nephroureterectomy (RNU) represents the standard of care for high grade upper tract urothelial carcinoma (UTUC). Open and laparosc...

An independent assessment of an artificial intelligence system for prostate cancer detection shows strong diagnostic accuracy.

Prostate cancer is a leading cause of morbidity and mortality for adult males in the US. The diagnosis of prostate carcinoma is usually made on prosta...

Computer-aided diagnosis and regional segmentation of nasopharyngeal carcinoma based on multi-modality medical images.

PURPOSE: Nasopharyngeal carcinoma (NPC) is a category of tumors with high incidence in head-and-neck (H&N) body region, and the diagnosis and treatmen...

Deep learning-based six-type classifier for lung cancer and mimics from histopathological whole slide images: a retrospective study.

BACKGROUND: Targeted therapy and immunotherapy put forward higher demands for accurate lung cancer classification, as well as benign versus malignant ...

Development and evaluation of a deep neural network for histologic classification of renal cell carcinoma on biopsy and surgical resection slides.

Renal cell carcinoma (RCC) is the most common renal cancer in adults. The histopathologic classification of RCC is essential for diagnosis, prognosis,...

Novel deep learning-based survival prediction for oral cancer by analyzing tumor-infiltrating lymphocyte profiles through CIBERSORT.

The tumor microenvironment (TME) within mucosal neoplastic tissue in oral cancer (ORCA) is greatly influenced by tumor-infiltrating lymphocytes (TILs)...

Characterizing the function of domain linkers in regulating the dynamics of multi-domain fusion proteins by microsecond molecular dynamics simulations and artificial intelligence.

Multi-domain proteins are not only formed through natural evolution but can also be generated by recombinant DNA technology. Because many fusion prote...

A comparison of surgical outcomes among robotic cases performed with an employed surgical assist versus a second surgeon as the assist.

To examine whether utilizing an employed surgical first assistant or a physician as an assistant during gynecologic robotic cases affects surgical var...

Reperfusion Therapy in Acute Ischemic Stroke with Active Cancer: A Meta-Analysis Aided by Machine Learning.

OBJECTIVES: While the prevalence of active cancer patients experiencing acute stroke is increasing, the effects of active cancer on reperfusion therap...

Explainable machine learning can outperform Cox regression predictions and provide insights in breast cancer survival.

Cox Proportional Hazards (CPH) analysis is the standard for survival analysis in oncology. Recently, several machine learning (ML) techniques have bee...

Collaborative Robotic Assistant Platform for Endonasal Surgery: Preliminary In-Vitro Trials.

Endonasal surgery is a minimally invasive approach for the removal of pituitary tumors (sarcomas). In this type of procedure, the surgeon has to compl...

Current applications of deep-learning in neuro-oncological MRI.

PURPOSE: Magnetic Resonance Imaging (MRI) provides an essential contribution in the screening, detection, diagnosis, staging, treatment and follow-up ...

Predicting treatment response from longitudinal images using multi-task deep learning.

Radiographic imaging is routinely used to evaluate treatment response in solid tumors. Current imaging response metrics do not reliably predict the un...

Drug ranking using machine learning systematically predicts the efficacy of anti-cancer drugs.

Artificial intelligence and machine learning (ML) promise to transform cancer therapies by accurately predicting the most appropriate therapies to tre...

Artificial neural networks versus LASSO regression for the prediction of long-term survival after surgery for invasive IPMN of the pancreas.

Prediction of long-term survival in patients with invasive intraductal papillary mucinous neoplasm (IPMN) of the pancreas may aid in patient assessmen...