Oncology/Hematology

Virtual Biopsy by Using Artificial Intelligence-based Multimodal Modeling of Binational Mammography Data.

Background Computational models based on artificial intelligence (AI) are increasingly used to diagnose malignant breast lesions. However, assessment from radiologic images of the specific pathologic lesion subtypes, as detailed in the results of biopsy procedures, remains a challenge. Purpose To develop an AI-based model to identify breast lesion subtypes with mammograms and linked electronic hea...

D-CryptO: deep learning-based analysis of colon organoid morphology from brightfield images.

Stem cell-derived organoids are a promising tool to model native human tissues as they resemble human organs functionally and structurally compared to traditional monolayer cell-based assays. For instance, colon organoids can spontaneously develop crypt-like structures similar to those found in the native colon. While analyzing the structural development of organoids can be a valuable readout, usi...

Deep learning detector for high precision monitoring of cell encapsulation statistics in microfluidic droplets.

Encapsulation of cells inside microfluidic droplets is central to several applications involving cellular analysis. Although, theoretically the encaps...

Perioperative Red Cell Line Trend following Robot-Assisted Radical Prostatectomy for Prostate Cancer.

Background and Objective: Blood loss represents a long-standing concern of radical prostatectomy (RP). This study aimed to assess how red line cell va...

Survival analysis of localized prostate cancer with deep learning.

In recent years, data-driven, deep-learning-based models have shown great promise in medical risk prediction. By utilizing the large-scale Electronic ...

A Deep Learning-Based Computer Aided Detection (CAD) System for Difficult-to-Detect Brain Metastases.

PURPOSE: We sought to develop a computer-aided detection (CAD) system that optimally augments human performance, excelling especially at identifying s...

Raman spectroscopy combined with deep learning for rapid detection of melanoma at the single cell level.

Melanoma is an aggressive and metastatic skin cancer caused by genetic mutations in melanocytes, and its incidence is increasing year by year. Underst...

Staging Paro: The care of making robot(s) care.

Paro, a baby seal robot, is arguably the best-known care robot worldwide. Its clinical effects on people with special needs have been studied for more...

Kidney Tumor Detection and Classification Based on Deep Learning Approaches: A New Dataset in CT Scans.

Kidney tumor (KT) is one of the diseases that have affected our society and is the seventh most common tumor in both men and women worldwide. The earl...

Clinical target volume segmentation based on gross tumor volume using deep learning for head and neck cancer treatment.

Accurate clinical target volume (CTV) delineation is important for head and neck intensity-modulated radiation therapy. However, delineation is time-c...

Intraoperative near-infrared lymphography with indocyanine green may aid lymph node dissection during robot-assisted resection of gastroesophageal junction cancer.

BACKGROUND: Adequate lymphadenectomy during gastroesophageal junction (GEJ) cancer resection is essential, because lymph node (LN) metastasis correlat...

Input feature design and its impact on the performance of deep learning models for predicting fluence maps in intensity-modulated radiation therapy.

. Deep learning (DL) models for fluence map prediction (FMP) have great potential to reduce treatment planning time in intensity-modulated radiation t...

Deep learning diagnostics for bladder tumor identification and grade prediction using RGB method.

We evaluate the diagnostic performance of deep learning artificial intelligence (AI) for bladder cancer, which used white-light images (WLIs) and narr...

Automated classification of estrous stage in rodents using deep learning.

The rodent estrous cycle modulates a range of biological functions, from gene expression to behavior. The cycle is typically divided into four stages,...

Development and Evaluation of Machine Learning-Based High-Cost Prediction Model Using Health Check-Up Data by the National Health Insurance Service of Korea.

In this study, socioeconomic, medical treatment, and health check-up data from 2010 to 2017 of the National Health Insurance Service (NHIS) of Korea w...

Construction of VGG16 Convolution Neural Network (VGG16_CNN) Classifier with NestNet-Based Segmentation Paradigm for Brain Metastasis Classification.

Brain metastases (BMs) happen often in patients with metastatic cancer (MC), requiring initial and precise diagnosis of BMs, which remains important f...

Applying interpretable machine learning workflow to evaluate exposure-response relationships for large-molecule oncology drugs.

The application of logistic regression (LR) and Cox Proportional Hazard (CoxPH) models are well-established for evaluating exposure-response (E-R) rel...

Thyroid Nodules on Ultrasound in Children and Young Adults: Comparison of Diagnostic Performance of Radiologists' Impressions, ACR TI-RADS, and a Deep Learning Algorithm.

In current clinical practice, thyroid nodules in children are generally evaluated on the basis of radiologists' overall impressions of ultrasound ima...

Deep learning with biopsy whole slide images for pretreatment prediction of pathological complete response to neoadjuvant chemotherapy in breast cancer：A multicenter study.

INTRODUCTION: Predicting pathological complete response (pCR) for patients receiving neoadjuvant chemotherapy (NAC) is crucial in establishing individ...

Comparison of Early Urinary Continence, Oncological Outcomes, and Postoperative Complications in Retzius-Sparing and Standard Approach Robot-Assisted Radical Prostatectomy.

The aim of the study is to compare the results of early urinary continence (UC), pathological results, console time (CT), and perioperative morbidity...