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Surveys

Latest AI and machine learning research in surveys for healthcare professionals.

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CEGAN: Classification Enhancement Generative Adversarial Networks for unraveling data imbalance problems.

The data imbalance problem in classification is a frequent but challenging task. In real-world datas...

Improving data acquisition speed and accuracy in sport using neural networks.

Video analysis is used in sport to derive kinematic variables of interest but often relies on time-c...

Artificial Intelligence in Screening Mammography: A Population Survey of Women's Preferences.

OBJECTIVE: To investigate the general population's view on the use of artificial intelligence (AI) f...

IoT in the Wake of COVID-19: A Survey on Contributions, Challenges and Evolution.

The novel coronavirus (COVID-19), declared by the World Health Organization (WHO) as a global pandem...

US primary care in 2029: A Delphi survey on the impact of machine learning.

OBJECTIVE: To solicit leading health informaticians' predictions about the impact of AI/ML on primar...

Theoretical analysis and experimental validation of volume bias of soft Dice optimized segmentation maps in the context of inherent uncertainty.

The clinical interest is often to measure the volume of a structure, which is typically derived from...

The automation of bias in medical Artificial Intelligence (AI): Decoding the past to create a better future.

Medicine is at a disciplinary crossroads. With the rapid integration of Artificial Intelligence (AI)...

Investigating Pain-Related Avoidance Behavior using a Robotic Arm-Reaching Paradigm.

Avoidance behavior is a key contributor to the transition from acute pain to chronic pain disability...

How to read and review papers on machine learning and artificial intelligence in radiology: a survival guide to key methodological concepts.

In recent years, there has been a dramatic increase in research papers about machine learning (ML) a...

Reinforcement learning for intelligent healthcare applications: A survey.

Discovering new treatments and personalizing existing ones is one of the major goals of modern clini...

DeepRescore: Leveraging Deep Learning to Improve Peptide Identification in Immunopeptidomics.

The identification of major histocompatibility complex (MHC)-binding peptides in mass spectrometry (...

Deep neural network models for computational histopathology: A survey.

Histopathological images contain rich phenotypic information that can be used to monitor underlying ...

One Algorithm May Not Fit All: How Selection Bias Affects Machine Learning Performance.

Machine learning (ML) algorithms have demonstrated high diagnostic accuracy in identifying and categ...

Biological batch normalisation: How intrinsic plasticity improves learning in deep neural networks.

In this work, we present a local intrinsic rule that we developed, dubbed IP, inspired by the Infoma...

Unveiling COVID-19 from CHEST X-Ray with Deep Learning: A Hurdles Race with Small Data.

The possibility to use widespread and simple chest X-ray (CXR) imaging for early screening of COVID-...

A survey of multiscale modeling: Foundations, historical milestones, current status, and future prospects.

Research problems in the domains of physical, engineering, biological sciences often span multiple t...

An Artificial Neural Network Model for Assessing Frailty-Associated Factors in the Thai Population.

Frailty, one of the major public health problems in the elderly, can result from multiple etiologic ...

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