Ovarian Cancer

Computational Pathology for Accurate Prediction of Breast Cancer Recurrence: Development and Validation of a Deep Learning-based Tool

Accurate recurrence risk stratification is crucial for optimizing treatment plans for breast cancer patients. Current prognostic tools like Oncotype DX (ODX) offer valuable genomic insights for HR+/HER2- patients but are limited by cost and accessibility, particularly in underserved populations. In this study, we present Deep-BCR-Auto, a deep learning-based computational pathology approach that ...

Development and validation of an explainable machine learning model for predicting multidimensional frailty in hospitalized patients with cirrhosis.

We sought to develop and validate a machine learning (ML) model for predicting multidimensional frailty based on clinical and laboratory data. Moreover, an explainable ML model utilizing SHapley Additive exPlanations (SHAP) was constructed. This study enrolled 622 patients hospitalized due to decompensating episodes at a tertiary hospital. The cohort data were randomly divided into training and te...

Automated detection of underdiagnosed medical conditions via opportunistic imaging

Abdominal computed tomography (CT) scans are frequently performed in clinical settings. Opportunistic CT involves repurposing routine CT images to e...

Deep Learning Segmentation of Ascites on Abdominal CT Scans for Automatic Volume Quantification.

Purpose To evaluate the performance of an automated deep learning method in detecting ascites and subsequently quantifying its volume in patients with...

Fluid Intelligence: AI's Role in Accurate Measurement of Ascites.

Validating linalool as a potential drug for breast cancer treatment based on machine learning and molecular docking.

Breast cancer (BC) is a common cancer for women. This study aims to construct a prognostic risk model of BC and identify prognostic biomarkers through...

Avelumab first-line maintenance in advanced urothelial carcinoma: Complete screening for prognostic and predictive factors using machine learning in the JAVELIN Bladder 100 phase 3 trial.

BACKGROUND: Avelumab first-line (1 L) maintenance is a standard of care for advanced urothelial carcinoma (aUC) based on the JAVELIN Bladder 100 phase...

[The Use of Platinum-Based Chemotherapy for Esophageal Cancer Patients with Impaired Renal Function].

INTRODUCTION: The key drugs of first-line chemotherapy for metastatic esophageal cancer are 5-FU and cisplatin(CF). However, the treatment strategy fo...

[A Case of Refractory Lymphatic Leakage after Robot-Assisted Radical Cystectomy].

A 78-year-old male visited the referring hospital because of asymptomatic gross hematuria. The patient was diagnosed with bladder cancer, clinical sta...

Chylous Ascites After Robot-Assisted Laparoscopic Donor Nephrectomy: Is Early Surgical Intervention Necessary?

OBJECTIVES: Chylous ascites is a rare complication that may occur after living donor nephrectomy. The continuous loss of lymphatics, which carries a h...

Hepatic Hydrothorax Without Ascites: A Diagnostic And Management Challenge.

Hepatic hydrothorax refers to the presence of a pleural effusion (usually >500 mL) in a patient with cirrhosis who does not have other reasons to have...

A Cascaded Deep Learning Framework for Segmentation of Nuclei in Digital Histology Images.

Accurate segmentation of nuclei is an essential step in analysis of digital histology images for diagnostic and prognostic applications. Despite recen...

Galvanostatically Deposited PtNi Thin-Films as Electrocatalysts for the Hydrogen Evolution Reaction.

The synthesis of hybrid platinum materials is fundamental to enable alkaline water electrolysis for cost-effective H generation. In this work, we have...

Detection of subtype-specific breast cancer surface protein biomarkers via a novel transcriptomics approach.

BACKGROUND: Cell-surface proteins have been widely used as diagnostic and prognostic markers in cancer research and as targets for the development of ...

Survey and comparative assessments of computational multi-omics integrative methods with multiple regulatory networks identifying distinct tumor compositions across pan-cancer data sets.

The significance of pan-cancer categories has recently been recognized as widespread in cancer research. Pan-cancer categorizes a cancer based on its ...

Micrometer-sized electrically programmable shape-memory actuators for low-power microrobotics.

Shape-memory actuators allow machines ranging from robots to medical implants to hold their form without continuous power, a feature especially advant...

Fully Automated Segmentation of Connective Tissue Compartments for CT-Based Body Composition Analysis: A Deep Learning Approach.

OBJECTIVE: Body composition comprises prognostic information in patients with various malignancies and can be opportunistically determined from routin...

[A Case of Jejunal Ectopic Pancreatic Cancer with Intestinal Perforation].

This patient was a 96-year-old woman. She was referred to our hospital with abdominal pain and vomiting. The levels of the tumor markers CEA and CA19-...

Prior to Initiation of Chemotherapy, Can We Predict Breast Tumor Response? Deep Learning Convolutional Neural Networks Approach Using a Breast MRI Tumor Dataset.

We hypothesize that convolutional neural networks (CNN) can be used to predict neoadjuvant chemotherapy (NAC) response using a breast MRI tumor datase...

and Antileishmanial Activity of a Compound Derived of Platinum, Oxaliplatin, against .

This study aimed to evaluate the antileishmanial efficacy of oxaliplatin against both and . The IC, CC, and SI of oxaliplatin against promastigotes...