AIMC Topic: Humans

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Relaxing Conservatism for Enhanced Impedance Range and Transparency in Haptic Interaction.

IEEE transactions on haptics
The Time Domain Passivity Approach (TDPA) has been accepted as one of least conservative tools for designing stabilizing controllers in haptics and teleoperation, but it still suffers from conservatism because it is based on passivity. Additionally, ...

Haptic Interactions Subject to Variable Latency.

IEEE transactions on haptics
Model-Mediated Teleoperation (MMT) between a haptic device and a remote or virtual environment uses a local model of the environment to compensate for latency of communication. MMT is often case-specific, and requires underlying latency distributions...

Can we predict pathology without surgery? Weighing the added value of multiparametric MRI and whole prostate radiomics in integrative machine learning models.

European radiology
OBJECTIVE: To test the ability of high-performance machine learning (ML) models employing clinical, radiological, and radiomic variables to improve non-invasive prediction of the pathological status of prostate cancer (PCa) in a large, single-institu...

Multiparametric MRI-Based Interpretable Radiomics Machine Learning Model Differentiates Medulloblastoma and Ependymoma in Children: A Two-Center Study.

Academic radiology
RATIONALE AND OBJECTIVES: Medulloblastoma (MB) and Ependymoma (EM) in children, share similarities in age group, tumor location, and clinical presentation. Distinguishing between them through clinical diagnosis is challenging. This study aims to expl...

Novel Technologies in Artificial Intelligence and Telemedicine for Glaucoma Screening.

Journal of glaucoma
PURPOSE: To provide an overview of novel technologies in telemedicine and artificial intelligence (AI) approaches for cost-effective glaucoma screening.

A hybrid EEG classification model using layered cascade deep learning architecture.

Medical & biological engineering & computing
The problem of multi-class classification is always a challenge in the field of EEG (electroencephalogram)-based seizure detection. The traditional studies focus on computing or learning a set of features from EEG to distinguish between different pat...

Diagnosing schizophrenia using deep learning: Novel interpretation approaches and multi-site validation.

Brain research
Schizophrenia is a profound and enduring mental disorder that imposes significant negative impacts on individuals, their families, and society at large. The development of more accurate and objective diagnostic tools for schizophrenia can be expedite...

Financial impact of incorporating deep learning reconstruction into magnetic resonance imaging routine.

European journal of radiology
PURPOSE: Artificial intelligence and deep learning solutions are increasingly utilized in healthcare and radiology. The number of studies addressing their enhancement of productivity and monetary impact is, however, still limited. Our hospital has fa...

Outline and background for the EU-OS solubility prediction challenge.

SLAS discovery : advancing life sciences R & D
In June 2022, EU-OS came to the decision to make public a solubility data set of 100+K compounds obtained from several of the EU-OS proprietary screening compound collections. Leveraging on the interest of SLAS for screening scientific development it...