Devices and Vaccines

Improvement of Neoantigen Identification Through Convolution Neural Network.

Accurate prediction of neoantigens and the subsequent elicited protective anti-tumor response are particularly important for the development of cancer vaccine and adoptive T-cell therapy. However, current algorithms for predicting neoantigens are limited by binding affinity data and algorithmic constraints, inevitably resulting in high false positives. In this study, we proposed a deep convolutio...

A deep learning approach for dental implant planning in cone-beam computed tomography images.

BACKGROUND: The aim of this study was to evaluate the success of the artificial intelligence (AI) system in implant planning using three-dimensional cone-beam computed tomography (CBCT) images.

Extracting Adverse Drug Events from Clinical Notes.

Adverse drug events (ADEs) are unexpected incidents caused by the administration of a drug or medication. To identify and extract these events, we req...

Male pelvic multi-organ segmentation on transrectal ultrasound using anchor-free mask CNN.

PURPOSE: Current prostate brachytherapy uses transrectal ultrasound images for implant guidance, where contours of the prostate and organs-at-risk are...

Deep Learning Model for Automated Detection and Classification of Central Canal, Lateral Recess, and Neural Foraminal Stenosis at Lumbar Spine MRI.

Background Assessment of lumbar spinal stenosis at MRI is repetitive and time consuming. Deep learning (DL) could improve -productivity and the consis...

A method for utilizing automated machine learning for histopathological classification of testis based on Johnsen scores.

We examined whether a tool for determining Johnsen scores automatically using artificial intelligence (AI) could be used in place of traditional Johns...

AI-based Strategies to Reduce Workload in Breast Cancer Screening with Mammography and Tomosynthesis: A Retrospective Evaluation.

Background The workflow of breast cancer screening programs could be improved given the high workload and the high number of false-positive and false-...

Machine learning-assisted immune profiling stratifies peri-implantitis patients with unique microbial colonization and clinical outcomes.

The endemic of peri-implantitis affects over 25% of dental implants. Current treatment depends on empirical patient and site-based stratifications an...

Overcoming Immunological Challenges Limiting Capsid-Mediated Gene Therapy With Machine Learning.

A key hurdle to making adeno-associated virus (AAV) capsid mediated gene therapy broadly beneficial to all patients is overcoming pre-existing and the...

Urine leak after robotic radical prostatectomy: not all urine leaks come from the anastomosis.

Radical prostatectomy is the gold standard in patients that are surgical candidates with localized prostate cancer. While most postoperative urine lea...

Integrated Random Negative Sampling and Uncertainty Sampling in Active Learning Improve Clinical Drug Safety Drug-Drug Interaction Information Retrieval.

Clinical drug-drug interactions (DDIs) have been a major cause for not only medical error but also adverse drug events (ADEs). The published literatur...

A controlled human infection model of Streptococcus pyogenes pharyngitis (CHIVAS-M75): an observational, dose-finding study.

BACKGROUND: Streptococcus pyogenes is a leading cause of infection-related morbidity and mortality. A reinvigorated vaccine development effort calls f...

Prediction of Coronary Stent Underexpansion by Pre-Procedural Intravascular Ultrasound-Based Deep Learning.

OBJECTIVES: The aim of this study was to develop pre-procedural intravascular ultrasound (IVUS)-based models for predicting the occurrence of stent un...

Dielectric Engineered Two-Dimensional Neuromorphic Transistors.

Two-dimensional (2D) materials, which exhibit planar-wafer technique compatibility and pure electrically triggered communication, have established the...

A biomimetic neural encoder for spiking neural network.

Spiking neural networks (SNNs) promise to bridge the gap between artificial neural networks (ANNs) and biological neural networks (BNNs) by exploiting...

Consolidated domain adaptive detection and localization framework for cross-device colonoscopic images.

Automatic polyp detection has been proven to be crucial in improving the diagnosis accuracy and reducing colorectal cancer mortality during the precan...

Artificial Intelligence-Enabled Analysis of Public Attitudes on Facebook and Twitter Toward COVID-19 Vaccines in the United Kingdom and the United States: Observational Study.

BACKGROUND: Global efforts toward the development and deployment of a vaccine for COVID-19 are rapidly advancing. To achieve herd immunity, widespread...

Three-dimensional image volumes from two-dimensional digitally reconstructed radiographs: A deep learning approach in lower limb CT scans.

PURPOSE: Three-dimensional (3D) reconstructions of the human anatomy have been available for surgery planning or diagnostic purposes for a few years n...

Automated optimization of double heater convective polymerase chain reaction devices based on CFD simulation database and artificial neural network model.

This paper presents a framework for automated optimization of double-heater convective PCR (DH-cPCR) devices by developing a computational fluid dynam...

Machine learning analysis of pregnancy data enables early identification of a subpopulation of newborns with ASD.

To identify newborns at risk of developing ASD and to detect ASD biomarkers early after birth, we compared retrospectively ultrasound and biological m...