Bioterrorism

Deep learning-extracted CT imaging phenotypes predict response to total resection in colorectal cancer.

BACKGROUND: Deep learning surpasses many traditional methods for many vision tasks, allowing the tra...

The assessment of response surface methodology (RSM) and artificial neural network (ANN) modeling in dry flue gas desulfurization at low temperatures.

The performance of a flue gas desulfurization (FGD) system is characterized by SO removal efficiency...

Molecular MRI-Based Monitoring of Cancer Immunotherapy Treatment Response.

Immunotherapy constitutes a paradigm shift in cancer treatment. Its FDA approval for several indicat...

Quasi-synchronization of drive-response systems with parameter mismatch via event-triggered impulsive control.

In this paper, an event-triggered impulsive control method is proposed to investigate the quasi-sync...

Response to: 'Deep learning synthetic angiograms for individuals unable to undergo contrast-guided laser treatment in aggressive retinopathy of prematurity'.

Prediction of pathologic complete response to neoadjuvant systemic therapy in triple negative breast cancer using deep learning on multiparametric MRI.

Triple-negative breast cancer (TNBC) is an aggressive subtype of breast cancer. Neoadjuvant systemic...

Using Deep Learning to Predict Treatment Response in Patients with Hepatocellular Carcinoma Treated with Y90 Radiation Segmentectomy.

Treatment of hepatocellular carcinoma (HCC) with Y90 radioembolization segmentectomy (Y90-RE) demons...

Multistain deep learning for prediction of prognosis and therapy response in colorectal cancer.

Although it has long been known that the immune cell composition has a strong prognostic and predict...

Deep learning prediction of pathological complete response, residual cancer burden, and progression-free survival in breast cancer patients.

The goal of this study was to employ novel deep-learning convolutional-neural-network (CNN) to predi...

Energy saving strategy of cloud data computing based on convolutional neural network and policy gradient algorithm.

Cloud Data Computing (CDC) is conducive to precise energy-saving management of user data centers bas...

In-silico generation of high-dimensional immune response data in patients using a deep neural network.

Technologies for single-cell profiling of the immune system have enabled researchers to extract rich...

ASO Author Reflections: Development of Natural Language Processing-Based Machine-Learning Algorithms to Identify Pathologic Complete Response from Surgical Pathology Reports.

Deep Learning-Based Objective and Reproducible Osteosarcoma Chemotherapy Response Assessment and Outcome Prediction.

Osteosarcoma is the most common primary bone cancer, whose standard treatment includes pre-operative...

Plasma cell subtypes analyzed using artificial intelligence algorithm for predicting biochemical recurrence, immune escape potential, and immunotherapy response of prostate cancer.

BACKGROUND: Plasma cells as an important component of immune microenvironment plays a crucial role i...

Automatic segmentation of hepatic metastases on DWI images based on a deep learning method: assessment of tumor treatment response according to the RECIST 1.1 criteria.

BACKGROUND: Evaluation of treated tumors according to Response Evaluation Criteria in Solid Tumors (...

Improving the accuracy of single-trial fMRI response estimates using GLMsingle.

Advances in artificial intelligence have inspired a paradigm shift in human neuroscience, yielding l...

Analysis and estimation of cross-flow heat exchanger fouling in phosphoric acid concentration plant using response surface methodology (RSM) and artificial neural network (ANN).

The production of phosphoric acid by dehydrated process leads to the precipitation of unwanted insol...

Identification of agricultural quarantine materials in passenger's luggage using ion mobility spectroscopy combined with a convolutional neural network.

As economic globalization intensifies, the recent increase in agricultural products and travelers fr...

An Introduction to Artificial Intelligence in Developmental and Behavioral Pediatrics.

Technological breakthroughs, together with the rapid growth of medical information and improved data...

An integrated deep learning model for the prediction of pathological complete response to neoadjuvant chemotherapy with serial ultrasonography in breast cancer patients: a multicentre, retrospective study.

BACKGROUND: The biological phenotype of tumours evolves during neoadjuvant chemotherapy (NAC). Accur...

Deep Learning Prediction of Pathologic Complete Response in Breast Cancer Using MRI and Other Clinical Data: A Systematic Review.

Breast cancer patients who have pathological complete response (pCR) to neoadjuvant chemotherapy (NA...