Ethics

A machine learning method for predicting the probability of MODS using only non-invasive parameters.

OBJECTIVES: Timely and accurate prediction of multiple organ dysfunction syndrome (MODS) is essentia...

Non-Local Graph Neural Networks.

Modern graph neural networks (GNNs) learn node embeddings through multilayer local aggregation and a...

Pharmacological, Non-Pharmacological Policies and Mutation: An Artificial Intelligence Based Multi-Dimensional Policy Making Algorithm for Controlling the Casualties of the Pandemic Diseases.

Fighting against the pandemic diseases with unique characters requires new sophisticated approaches ...

Deep learning to estimate durable clinical benefit and prognosis from patients with non-small cell lung cancer treated with PD-1/PD-L1 blockade.

Different biomarkers based on genomics variants have been used to predict the response of patients t...

An Open Source Replication of a Winning Recidivism Prediction Model.

We present results of our winning solution to the National Institute of Justice recidivism forecasti...

Uncertainty-informed deep learning models enable high-confidence predictions for digital histopathology.

A model's ability to express its own predictive uncertainty is an essential attribute for maintainin...

Non-Local Temporal Difference Network for Temporal Action Detection.

As an important part of video understanding, temporal action detection (TAD) has wide application sc...

Identification and Improvement of Hazard Scenarios in Non-Motorized Transportation Using Multiple Deep Learning and Street View Images.

In the prioritized vehicle traffic environment, motorized transportation has been obtaining more spa...

Automatic identification of early ischemic lesions on non-contrast CT with deep learning approach.

Early ischemic lesion on non-contrast computed tomogram (NCCT) in acute stroke can be subtle and nee...

Trends in segmentectomy for the treatment of stage 1A non-small cell lung cancers: Does the robot have an impact?

OBJECTIVES: Lobectomy may unnecessarily resect healthy lung parenchyma in Stage 1A non-small cell lu...

Deep-learning-based hepatic fat assessment (DeHFt) on non-contrast chest CT and its association with disease severity in COVID-19 infections: A multi-site retrospective study.

BACKGROUND: Hepatic steatosis (HS) identified on CT may provide an integrated cardiometabolic and CO...

An AI Bill of Rights: Implications for Health Care AI and Machine Learning-A Bioethics Lens.

Misplaced Trust and Distrust: How Not to Engage with Medical Artificial Intelligence.

Artificial intelligence (AI) plays a rapidly increasing role in clinical care. Many of these systems...

OpenFL: the open federated learning library.

Federated learning (FL) is a computational paradigm that enables organizations to collaborate on mac...

Deep Learning-Based Energy Expenditure Estimation in Assisted and Non-Assisted Gait Using Inertial, EMG, and Heart Rate Wearable Sensors.

Energy expenditure is a key rehabilitation outcome and is starting to be used in robotics-based reha...

CTRR-ncRNA: A Knowledgebase for Cancer Therapy Resistance and Recurrence Associated Non-coding RNAs.

Cancer therapy resistance and recurrence (CTRR) are the dominant causes of death in cancer patients....

Network Threat Detection Using Machine/Deep Learning in SDN-Based Platforms: A Comprehensive Analysis of State-of-the-Art Solutions, Discussion, Challenges, and Future Research Direction.

A revolution in network technology has been ushered in by software defined networking (SDN), which m...

Multiple Sclerosis Diagnosis Using Machine Learning and Deep Learning: Challenges and Opportunities.

Multiple Sclerosis (MS) is a disease that impacts the central nervous system (CNS), which can lead t...

Differentiation of eosinophilic and non-eosinophilic chronic rhinosinusitis on preoperative computed tomography using deep learning.

OBJECTIVES: This study aimed to develop deep learning (DL) models for differentiating between eosino...

Fast and Non-Destructive Quail Egg Freshness Assessment Using a Thermal Camera and Deep Learning-Based Air Cell Detection Algorithms for the Revalidation of the Expiration Date of Eggs.

Freshness is one of the most important parameters for assessing the quality of avian eggs. Available...

Robotic Non-Destructive Testing.

Non-destructive testing (NDT) and evaluation (NDE) are commonly referred to as the vast group of ana...