Other Cancers

Identifying Goals of Care Conversations in the Electronic Health Record Using Natural Language Processing and Machine Learning.

CONTEXT: Goals-of-care discussions are an important quality metric in palliative care. However, goal...

Radiomic analysis of magnetic resonance imaging predicts brain metastases velocity and clinical outcome after upfront radiosurgery.

BACKGROUND: Brain metastasis velocity (BMV) predicts outcomes after initial distant brain failure (D...

Biomarkers of the Response to Immune Checkpoint Inhibitors in Metastatic Urothelial Carcinoma.

The mechanisms underlying the resistance to immune checkpoint inhibitors (ICIs) therapy in metastati...

Case of slowly progressive type 1 diabetes mellitus with drastically reduced insulin secretory capacity after immune checkpoint inhibitor treatment for advanced renal cell carcinoma.

We encountered a 55-year-old Japanese man with advanced renal cell carcinoma and slowly progressive ...

Development of Convolutional Neural Networks to identify bone metastasis for prostate cancer patients in bone scintigraphy.

OBJECTIVE: The main aim of this work is to build a robust Convolutional Neural Network (CNN) algorit...

Calculation of immune cell proportion from batch tumor gene expression profile based on support vector regression.

In addition to tumor cells, a large number of immune cells are found in the tumor microenvironment (...

ANTIPROLIFERATIVE PROPERTIES OF ETHANOLIC AND AQUEOUS GRAVIOLA LEAF EXTRACTS ON TONGUE SQUAMOUS CELL CARCINOMA CELL LINE-25.

BACKGROUND: commonly known as Graviola, soursop or guanabana, is an evergreen tree native to the tr...

Digital health innovation to integrate palliative care during the COVID-19 pandemic.

Using Deep Learning with Convolutional Neural Network Approach to Identify the Invasion Depth of Endometrial Cancer in Myometrium Using MR Images: A Pilot Study.

Myometrial invasion affects the prognosis of endometrial cancer. However, discrepancies exist betwee...

Deep computational pathology in breast cancer.

Deep Learning (DL) algorithms are a set of techniques that exploit large and/or complex real-world d...

Artificial intelligence-assisted cytology for detection of cervical intraepithelial neoplasia or invasive cancer: A multicenter, clinical-based, observational study.

OBJECTIVE: Artificial intelligence (AI) could automatedly detect abnormalities in digital cytologica...

Quantifying the Brain Metastatic Tumor Micro-Environment using an Organ-On-A Chip 3D Model, Machine Learning, and Confocal Tomography.

Brain metastases are the most lethal cancer lesions; 10-30% of all cancers metastasize to the brain,...

Machine Learning Algorithms for Early Detection of Bone Metastases in an Experimental Rat Model.

Machine learning (ML) algorithms permit the integration of different features into a model to perfor...

Deep Learning Modeling of Androgen Receptor Responses to Prostate Cancer Therapies.

Gain-of-function mutations in human androgen receptor (AR) are among the major causes of drug resist...

Identification of intraductal carcinoma of the prostate on tissue specimens using Raman micro-spectroscopy: A diagnostic accuracy case-control study with multicohort validation.

BACKGROUND: Prostate cancer (PC) is the most frequently diagnosed cancer in North American men. Path...

Bone metastasis classification using whole body images from prostate cancer patients based on convolutional neural networks application.

Bone metastasis is one of the most frequent diseases in prostate cancer; scintigraphy imaging is par...

The deep learning model combining CT image and clinicopathological information for predicting ALK fusion status and response to ALK-TKI therapy in non-small cell lung cancer patients.

PURPOSE: This study aimed to investigate the deep learning model (DLM) combining computed tomography...

Deep Learning for Pediatric Posterior Fossa Tumor Detection and Classification: A Multi-Institutional Study.

BACKGROUND AND PURPOSE: Posterior fossa tumors are the most common pediatric brain tumors. MR imagin...

Deep learning-based survival analysis for brain metastasis patients with the national cancer database.

PURPOSE: Prognostic indices such as the Brain Metastasis Graded Prognostic Assessment have been used...

Classification of cervical neoplasms on colposcopic photography using deep learning.

Colposcopy is widely used to detect cervical cancers, but experienced physicians who are needed for ...

Artificial neural network model for preoperative prediction of severe liver failure after hemihepatectomy in patients with hepatocellular carcinoma.

BACKGROUND: Posthepatectomy liver failure is a worrisome complication after major hepatectomy for he...