Ovarian Cancer

Rethinking cancer of unknown primary: from diagnostic challenge to targeted treatment.

Cancer of unknown primary (CUP) is a metastatic malignancy for which a primary site of origin cannot...

Plasmonic Fiber Optic Sensing Platform for Point-of-Care Pharmacokinetic Monitoring of Platinum Chemotherapeutics: Toward Ultratrace Multi-omics Precision Chemotherapy Management.

Precision chemotherapy management requires efficient and ultrasensitive dynamic monitoring of drug p...

Automatic segmentation of liver structures in multi-phase MRI using variants of nnU-Net and Swin UNETR.

Accurate segmentation of the liver parenchyma, portal veins, hepatic veins, and lesions from MRI is ...

Using Data Mining to Differentiate Dengue with Warning Signs from Severe Dengue: A Predictive Model from Oaxaca, Mexico.

Dengue with warning signs (DWS) and severe dengue are significant public health concerns in tropical...

Generative AI in hepatology: Transforming multimodal patient-generated data into actionable insights.

Cirrhosis care is inherently complex, marked by a high risk of acute decompensation and significant ...

Modeling the prediction of spontaneous rupture and bleeding in hepatocellular carcinoma via machine learning algorithms.

This study aimed to identify the risk factors associated with spontaneous rupture and bleeding in he...

3Mont: A multi-omics integrative tool for breast cancer subtype stratification.

Breast Cancer (BRCA) is a heterogeneous disease, and it is one of the most prevalent cancer types am...

Microrobots for Antibiotic-Resistant Skin Colony Eradication.

Self-propelled nano- and micromachines have immense potential as autonomous seek-and-act devices in ...

Split DNA Tetrahedron-Mediated Spatiotemporal-Hierarchy CRISPR Cascade Integrated with Au@Pt Nanolabels and Artificial Intelligence for a Cervical Cancer MicroRNA Bioassay.

The screening and monitoring of microRNAs as cancer molecular biomarkers is clinically significant, ...

Pisces: A multi-modal data augmentation approach for drug combination synergy prediction.

Drug combination therapy is promising for cancer treatment by reducing resistance and improving effi...

Identification and validation of prognostic genes associated with T-cell exhaustion and macrophage polarization in breast cancer.

BACKGROUND: The most frequent malignant tumor in women is breast cancer (BRCA). It has been discover...

HR-SC-an academic-developed machine learning framework to classify HRD-positive ovarian cancer patients and predict sensitivity to olaparib.

BACKGROUND: High-grade serous ovarian cancer (OC) patients with defects in the homologous recombinat...

Development of a Transferable Density-Functional Tight-Binding Model for Organic Molecules at the Water/Platinum Interface.

A computationally efficient and transferable approach for modeling reactions at metal/water interfac...

Correction to "The Melamine-Driven Solvation Effect Promotes Oxygen Reduction on Platinum Catalyst: Machine Learning-Aided Free Energy Calculations".

Ovarian Cancer Detection in Ascites Cytology with Weakly Supervised Model on Nationwide Data Set.

Conventional ascitic fluid cytology for detecting ovarian cancer is limited by its low sensitivity. ...

Inhibiting Dissolution of Platinum with Atomic Rare Earth Bridged by Nitrogen to Boost Alkaline Hydrogen Evolution.

The unfavorable water dissociation and continuous dissolution of Pt single-atom catalysts significan...

Fullerene Network-Buffered Platinum Nanoparticles Toward Efficient and Stable Electrochemical Ammonia Oxidation Reaction for Hydrogen Production.

Green ammonia is a promising hydrogen carrier due to its well-established production, storage, and t...

Transforming breast cancer diagnosis and treatment with large language Models: A comprehensive survey.

Breast cancer (BrCa), being one of the most prevalent forms of cancer in women, poses many challenge...

Amogel: a multi-omics classification framework using associative graph neural networks with prior knowledge for biomarker identification.

The advent of high-throughput sequencing technologies, such as DNA microarray and DNA sequencing, ha...

Machine learning based intratumor heterogeneity related signature for prognosis and drug sensitivity in breast cancer.

Intratumor heterogeneity (ITH) is involved in tumor evolution and drug resistance. Drug sensitivity ...

Addressing Hemolysis-Induced Loss of Sensitivity in Lateral Flow Assays of Blood Samples with Platinum-Coated Gold Nanoparticles and Machine Learning.

Gold nanoparticles (GNPs), which appear red, are widely used as labels in lateral flow assays (LFAs)...