Oncology/Hematology

Machine learning-based prediction of acute kidney injury after nephrectomy in patients with renal cell carcinoma.

The precise prediction of acute kidney injury (AKI) after nephrectomy for renal cell carcinoma (RCC)...

Machine Learning and Artificial Intelligence-driven Spatial Analysis of the Tumor Immune Microenvironment in Pathology Slides.

A better understanding of the tumor immune microenvironment (TIME) could lead to accurate diagnosis,...

Robotic versus laparoscopic right hemicolectomy: a case-matched study.

The current gold standard surgical treatment for right colonic malignancy is the laparoscopic right ...

Deep Learning Based Capsule Neural Network Model for Breast Cancer Diagnosis Using Mammogram Images.

Breast cancer is a commonly occurring disease in women all over the world. Mammogram is an efficient...

[Importance of conventional pancreas imaging: ultrasound, CT, and MRI. Facts and possibilities].

Modern imaging procedures, including CT and MR diagnostics, play a significant role in recognizing, ...

A stacking ensemble deep learning approach to cancer type classification based on TCGA data.

Cancer tumor classification based on morphological characteristics alone has been shown to have seri...

Application of Radiomics and Artificial Intelligence for Lung Cancer Precision Medicine.

Medical imaging is the standard-of-care for early detection, diagnosis, treatment planning, monitori...

Machine learning as the new approach in understanding biomarkers of suicidal behavior.

In psychiatry, compared to other medical fields, the identification of biological markers that would...

Design, synthesis and mechanistic study of new benzenesulfonamide derivatives as anticancer and antimicrobial agents carbonic anhydrase IX inhibition.

Changes in gene expression cause uncontrolled cell proliferation and consequently tumor hypoxia. The...

xDeep-AcPEP: Deep Learning Method for Anticancer Peptide Activity Prediction Based on Convolutional Neural Network and Multitask Learning.

Cancer is one of the leading causes of death worldwide. Conventional cancer treatment relies on radi...

A novel deep learning approach to extract Chinese clinical entities for lung cancer screening and staging.

BACKGROUND: Computed tomography (CT) reports record a large volume of valuable information about pat...

Robot-assisted enucleation of a giant submucosal tumor in the upper esophagus.

Few reports have demonstrated robotic surgery for large tumors in the upper esophagus. We report a c...

Mathematical and computational modeling for the determination of optical parameters of breast cancer cell.

This study enumerates the quantitative measurement of optical parameters used in several diagnostic ...

Improving personalized tumor growth predictions using a Bayesian combination of mechanistic modeling and machine learning.

BACKGROUND: In clinical practice, a plethora of medical examinations are conducted to assess the sta...

The use of a next-generation sequencing-derived machine-learning risk-prediction model (OncoCast-MPM) for malignant pleural mesothelioma: a retrospective study.

BACKGROUND: Current risk stratification for patients with malignant pleural mesothelioma based on di...

Deep Learning-Guided Fiberoptic Raman Spectroscopy Enables Real-Time Diagnosis and Assessment of Nasopharyngeal Carcinoma and Post-treatment Efficacy during Endoscopy.

In this work, we develop a deep learning-guided fiberoptic Raman diagnostic platform to assess its a...

In silico saturation mutagenesis of cancer genes.

Despite the existence of good catalogues of cancer genes, identifying the specific mutations of thos...

Machine learning predicts treatment sensitivity in multiple myeloma based on molecular and clinical information coupled with drug response.

Providing treatment sensitivity stratification at the time of cancer diagnosis allows better allocat...

Test clamp procedure in robot-assisted partial nephrectomy: is it a safe procedure?

We performed test clamp procedure in robot-assisted partial nephrectomy (RAPN) to prevent massive bl...

Robotic Excision of a Duodenal Gastrointestinal Stromal Tumor.

Distinguishing benign and malignant lesions on contrast-enhanced breast cone-beam CT with deep learning neural architecture search.

PURPOSE: To utilize a neural architecture search (NAS) approach to develop a convolutional neural ne...