Oncology/Hematology

"White bile" as a result of a malignant bile obstruction.

An 87-year-old female was admitted for endoscopic retrograde cholangiopancreatography (ERCP) due to obstructive jaundice. On admission, total bilirubin was 15 mg/dl at the expense of direct bilirubin, GOT 356 U/l mg/dl, GPT 174 U/l, FA 2,358 U/l and GGT 1,089 U/l. The ERCP showed a prominent, irregular, non-cannulable papilla, so a fistulotomy was performed, emitting a clear, non-mucous fluid. Bil...

Deep learning quantification of vascular pharmacokinetic parameters in mouse brain tumor models.

BACKGROUND: Dynamic contrast-enhanced (DCE) MRI is widely used to assess vascular perfusion and permeability in cancer. In small animal applications, conventional modeling of pharmacokinetic (PK) parameters from DCE MRI images is complex and time consuming. This study is aimed at developing a deep learning approach to fully automate the generation of kinetic parameter maps, Ktrans (volume transfer...

Machine learning on thyroid disease: a review.

This study reviews the recent progress of machine learning for the early diagnosis of thyroid disease. Based on the results of this review, different ...

GSEnet: feature extraction of gene expression data and its application to Leukemia classification.

Gene expression data is highly dimensional. As disease-related genes account for only a tiny fraction, a deep learning model, namely GSEnet, is propos...

PRODeepSyn: predicting anticancer synergistic drug combinations by embedding cell lines with protein-protein interaction network.

Although drug combinations in cancer treatment appear to be a promising therapeutic strategy with respect to monotherapy, it is arduous to discover ne...

Universal encoding of pan-cancer histology by deep texture representations.

Cancer histological images contain rich biological and clinical information, but quantitative representation can be problematic and has prevented the ...

[Experience of Thoracotomy and Robot-assisted Bronchial Sleeve Resection 
after Neoadjuvant Chemoimmunotherapy for Local Advanced Central Lung Cancer].

BACKGROUND: Immunoneoadjuvant therapy opens a new prospect for local advanced lung cancer. The aim of our study was to explore the safety and feasibil...

Automated classification of cytogenetic abnormalities in hematolymphoid neoplasms.

MOTIVATION: Algorithms for classifying chromosomes, like convolutional deep neural networks (CNNs), show promise to augment cytogeneticists' workflows...

Can Deep Learning Replace Gadolinium in Neuro-Oncology?: A Reader Study.

MATERIALS AND METHODS: This monocentric retrospective study leveraged 200 multiparametric brain MRIs acquired between November 2019 and February 2020 ...

International Validation of the SORG Machine-learning Algorithm for Predicting the Survival of Patients with Extremity Metastases Undergoing Surgical Treatment.

BACKGROUND: The Skeletal Oncology Research Group machine-learning algorithms (SORG-MLAs) estimate 90-day and 1-year survival in patients with long-bon...

Using Adversarial Images to Assess the Robustness of Deep Learning Models Trained on Diagnostic Images in Oncology.

PURPOSE: Deep learning (DL) models have rapidly become a popular and cost-effective tool for image classification within oncology. A major limitation ...

[Deep Learning-based Risk Prediction Model for Postoperative Healthcare-associated Infections].

Objective To develop a risk prediction model combining pre/intraoperative risk factors and intraoperative vital signs for postoperative healthcare-ass...

An app to classify a 5-year survival in patients with breast cancer using the convolutional neural networks (CNN) in Microsoft Excel: Development and usability study.

BACKGROUND: Breast cancer (BC) is the most common malignant cancer in women. A predictive model is required to predict the 5-year survival in patients...

Prediction of Early Symptom Remission in Two Independent Samples of First-Episode Psychosis Patients Using Machine Learning.

BACKGROUND: Validated clinical prediction models of short-term remission in psychosis are lacking. Our aim was to develop a clinical prediction model ...

Ultrasonographic morphological characteristics determined using a deep learning-based computer-aided diagnostic system of breast cancer.

To investigate the correlations between ultrasonographic morphological characteristics quantitatively assessed using a deep learning-based computer-ai...

epitope3D: a machine learning method for conformational B-cell epitope prediction.

The ability to identify antigenic determinants of pathogens, or epitopes, is fundamental to guide rational vaccine development and immunotherapies, wh...

Artificial intelligence in clinical research of cancers.

Several factors, including advances in computational algorithms, the availability of high-performance computing hardware, and the assembly of large co...

Machine Learning Approaches for Early Prostate Cancer Prediction Based on Healthcare Utilization Patterns.

The goal of this study was to build a machine learning model for early prostate cancer prediction based on healthcare utilization patterns. We examine...

ALLD: Acute Lymphoblastic Leukemia Detector.

Acute Lymphoblastic Leukemia (ALL) is a life-threatening type of cancer wherein mortality rate is unquestionably high. Early detection of ALL can redu...

Recent Developments in Artificial Intelligence-Based Techniques for Prostate Cancer Detection: A Scoping Review.

Artificial intelligence (AI) techniques can contribute to the early diagnosis of prostate cancer. Recently, there has been a sharp increase in the lit...