Risk Management

Artificial intelligence in cancer diagnostics and therapy: current perspectives.

Artificial intelligence (AI) has found its way into every sphere of human life including the field of medicine. Detection of cancer might be AI's most altruistic and convoluted challenge to date in the field of medicine. Embedding AI into various aspects of cancer diagnostics would be of immense use in dealing with the tedious, repetitive, time-consuming job of lesion detection, remove opportuniti...

The Regimen of Computed Tomography Screening for Lung Cancer: Lessons Learned Over 25 Years From the International Early Lung Cancer Action Program.

We learned many unanticipated and valuable lessons since we started planning our study of low-dose computed tomography (CT) screening for lung cancer in 1991. The publication of the baseline results of the Early Lung Cancer Action Project (ELCAP) in Lancet 1999 showed that CT screening could identify a high proportion of early, curable lung cancers. This stimulated large national screening studies...

Deep Neural Networks for Epistatic Sequence Analysis.

We report a step-by-step protocol to use pysster, a TensorFlow-based package for building deep neural networks on a broad range of epistatic sequences...

Protocol for Epistasis Detection with Machine Learning Using GenEpi Package.

To develop medical treatments and prevention, the association between disease and genetic variants needs to be identified. The main goal of genome-wid...

Unexpected Inequality: Disparate-Impact From Artificial Intelligence in Healthcare Decisions.

Systemic discrimination in healthcare plagues marginalized groups. Physicians incorrectly view people of color as having high pain tolerance, leading ...

Identification of Gene Regulatory Networks from Single-Cell Expression Data.

Single-cell RNAseq is an emerging technology that allows the quantification of gene expression in individual cells. In plants, single-cell sequencing ...

Cone Beam CT (CBCT) Based Synthetic CT Generation Using Deep Learning Methods for Dose Calculation of Nasopharyngeal Carcinoma Radiotherapy.

To generate synthetic CT (sCT) images with high quality from CBCT and planning CT (pCT) for dose calculation by using deep learning methods. 169 NPC...

Confronting pitfalls of AI-augmented molecular dynamics using statistical physics.

Artificial intelligence (AI)-based approaches have had indubitable impact across the sciences through the ability to extract relevant information from...

Application of artificial intelligence in screening for adverse perinatal outcomes: A protocol for systematic review.

The article presents a systematic review protocol. The aim of the study is an assessment of current studies regarding the application of artificial in...

AI technology for remote clinical assessment and monitoring.

OBJECTIVE: To report the clinical validation of an innovative, artificial intelligence (AI)-powered, portable and non-invasive medical device called W...

Network Building with the Cytoscape BioGateway App Explained in Five Use Cases.

The BioGateway App is a plugin for the Cytoscape network editor, allowing users to interactively build biological networks by querying the Biogateway ...

Robot-assisted minimally invasive thoracolaparoscopic esophagectomy versus open esophagectomy: long-term follow-up of a randomized clinical trial.

Initial results of the ROBOT, which randomized between robot-assisted minimally invasive esophagectomy (RAMIE) and open transthoracic esophagectomy (O...

Current Clinical Applications of Artificial Intelligence in Radiology and Their Best Supporting Evidence.

PURPOSE: Despite tremendous gains from deep learning and the promise of artificial intelligence (AI) in medicine to improve diagnosis and save costs, ...

Deep learning assisted differentiation of hepatocellular carcinoma from focal liver lesions: choice of four-phase and three-phase CT imaging protocol.

PURPOSE: To evaluate whether a three-phase dynamic contrast-enhanced CT protocol, when combined with a deep learning model, has similar accuracy in di...

Minimum information about clinical artificial intelligence modeling: the MI-CLAIM checklist.

[Rehabilitation of traumatic spinal cord injury with lower limb exoskeleton].

In recent years, several technological innovations have emerged to improve the rehabilitation of traumatic spinal cord injury (SCI). Among them, robot...

Estimation of Energy Absorption Capability of Arm Using Force Myography for Stable Human-Machine Interaction.

Human-robot interactions help in various industries and enhance the user experience in different ways. However, constant safety monitoring is needed i...

Outcomes of a Robot-Assisted Social-Emotional Understanding Intervention for Young Children with Autism Spectrum Disorders.

This study is a randomized control trial aimed at testing the role of a human-assisted social robot as an intervention mediator in a socio-emotional u...

An Approach to Robotic Testing of the Wrist Using Three-Dimensional Imaging and a Hybrid Testing Methodology.

Robotic technology is increasingly used for sophisticated in vitro testing designed to understand the subtleties of joint biomechanics. Typically, the...

Beyond the Artificial Intelligence Hype: What Lies Behind the Algorithms and What We Can Achieve.

The field of artificial intelligence (AI) is currently experiencing a period of extensive growth in a wide variety of fields, medicine not being the e...