Ovarian Cancer

Autonomous push button-controlled rapid insulin release from a piezoelectrically activated subcutaneous cell implant.

Traceless physical cues are desirable for remote control of the in situ production and real-time dosing of biopharmaceuticals in cell-based therapies. However, current optogenetic, magnetogenetic, or electrogenetic devices require sophisticated electronics, complex artificial intelligence-assisted software, and external energy supplies for power and control. Here, we describe a self-sufficient sub...

Nanocatalyst-Enabled Physically Unclonable Functions as Smart Anticounterfeiting Tags with AI-Aided Smartphone Authentication.

Counterfeiting is a worldwide issue affecting many industrial sectors, ranging from specialized technologies to retail market, such as fashion brands, pharmaceutical products, and consumer electronics. Counterfeiting is not only a huge economic burden (>$ 1 trillion losses/year), but it also represents a serious risk to human health, for example, due to the exponential increase of fake drugs and f...

Machine learning-based system for prediction of ascites grades in patients with liver cirrhosis using laboratory and clinical data: design and implementation study.

OBJECTIVES: The aim of the study was to implement a non-invasive model to predict ascites grades among patients with cirrhosis.

Reconstruction Algorithm-Based CT Imaging for the Diagnosis of Hepatic Ascites.

The study was aimed at exploring the diagnostic value of artificial intelligence reconstruction algorithm combined with CT image parameters on hepatic...

Experimental Voltammetry Analyzed Using Artificial Intelligence: Thermodynamics and Kinetics of the Dissociation of Acetic Acid in Aqueous Solution.

Artificial intelligence (AI) is used to quantitatively analyze the voltammetry of the reduction of acetic acid in aqueous solution generating thermody...

Automated Image Analysis for Single-Atom Detection in Catalytic Materials by Transmission Electron Microscopy.

Single-atom catalytic sites may have existed in all supported transition metal catalysts since their first application. Yet, interest in the design of...

From Mouse to Human: Cellular Morphometric Subtype Learned From Mouse Mammary Tumors Provides Prognostic Value in Human Breast Cancer.

Mouse models of cancer provide a powerful tool for investigating all aspects of cancer biology. In this study, we used our recently developed machine ...

Deep learning assisted distinguishing of honey seasonal changes using quadruple voltammetric electrodes.

The work presents innovative quadruple disk iridium, platinum, and iridium-platinum voltammetric electrodes with a special design, dedicated to the te...

A Deep Residual U-Net Algorithm for Automatic Detection and Quantification of Ascites on Abdominopelvic Computed Tomography Images Acquired in the Emergency Department: Model Development and Validation.

BACKGROUND: Detection and quantification of intra-abdominal free fluid (ie, ascites) on computed tomography (CT) images are essential processes for fi...

Identifying Cancer Subtypes Using a Residual Graph Convolution Model on a Sample Similarity Network.

Cancer subtype classification helps us to understand the pathogenesis of cancer and develop new cancer drugs, treatment from which patients would bene...

Byzantine-robust federated learning via credibility assessment on non-IID data.

Federated learning is a novel framework that enables resource-constrained edge devices to jointly learn a model, which solves the problem of data prot...

Evaluation of a Deep Learning Algorithm for Automated Spleen Segmentation in Patients with Conditions Directly or Indirectly Affecting the Spleen.

The aim of this study was to develop a deep learning-based algorithm for fully automated spleen segmentation using CT images and to evaluate the perfo...

Metal Nanoparticle Modified Carbon-Fiber Microelectrodes Enhance Adenosine Triphosphate Surface Interactions with Fast-Scan Cyclic Voltammetry.

Adenosine triphosphate (ATP) is an important rapid signaling molecule involved in a host of pathologies in the body. Historically, ATP is difficult to...

Artificial intelligence-based image analysis can predict outcome in high-grade serous carcinoma via histology alone.

High-grade extrauterine serous carcinoma (HGSC) is an aggressive tumor with high rates of recurrence, frequent chemotherapy resistance, and overall 5-...

A machine learning approach to identify predictive molecular markers for cisplatin chemosensitivity following surgical resection in ovarian cancer.

Ovarian cancer is associated with poor prognosis. Platinum resistance contributes significantly to the high rate of tumour recurrence. We aimed to ide...

Prediction and interpretation of cancer survival using graph convolution neural networks.

The survival rate of cancer has increased significantly during the past two decades for breast, prostate, testicular, and colon cancer, while the brai...

Utilization of circulating cell-free DNA profiling to guide first-line chemotherapy in advanced lung squamous cell carcinoma.

Platinum-based chemotherapy is one of treatment mainstay for patients with advanced lung squamous cell carcinoma (LUSC) but it is still a "one-size f...

Ultrashort echo time time-spatial labeling inversion pulse magnetic resonance angiography with denoising deep learning reconstruction for the assessment of abdominal visceral arteries.

Current contrast-enhanced magnetic resonance angiography (MRA) and non-contrast-enhanced balanced steady-state free precession (bSSFP) MRA cause susce...

Bioethics and healthcare policies. The benefit of using genetic tests of BRCA 1 and BRCA 2 in elderly patients.

This study focuses on the role of bioethics in designing public healthcare policies towards elderly patients with cancer. The general overview of publ...

Alcoholic liver disease: A registry view on comorbidities and disease prediction.

Alcoholic-related liver disease (ALD) is the cause of more than half of all liver-related deaths. Sustained excess drinking causes fatty liver and alc...