Machine learning applications to neuroimaging for glioma detection and classification: An artificial intelligence augmented systematic review

QD Buchlak, N Esmaili, JC Leveque, C Bennett… - Journal of Clinical …, 2021 - Elsevier
Glioma is the most common primary intraparenchymal tumor of the brain and the 5-year
survival rate of high-grade glioma is poor. Magnetic resonance imaging (MRI) is essential for …

Advances in artificial intelligence, robotics, augmented and virtual reality in neurosurgery

K Kazemzadeh, M Akhlaghdoust, A Zali - Frontiers in surgery, 2023 - frontiersin.org
Neurosurgical practitioners undergo extensive and prolonged training to acquire diverse
technical proficiencies, while neurosurgical procedures necessitate a substantial amount of …

[HTML][HTML] Digitalization in omnichannel healthcare supply chain businesses: The role of smart wearable devices

V Chang, QA Xu, K Hall, YA Wang, MM Kamal - Journal of Business …, 2023 - Elsevier
The advancement in technology has fostered the prevalence of the Internet of Things (IoT),
which enhances healthcare business quality, offers a seamless customer experience, and …

Artificial intelligence, machine learning, and deep learning for clinical outcome prediction

RW Pettit, R Fullem, C Cheng… - Emerging topics in life …, 2021 - portlandpress.com
AI is a broad concept, grouping initiatives that use a computer to perform tasks that would
usually require a human to complete. AI methods are well suited to predict clinical outcomes …

Artificial intelligence in neurosurgery: A state-of-the-art review from past to future

JA Tangsrivimol, E Schonfeld, M Zhang, A Veeravagu… - Diagnostics, 2023 - mdpi.com
In recent years, there has been a significant surge in discussions surrounding artificial
intelligence (AI), along with a corresponding increase in its practical applications in various …

Artificial intelligence and robotics in spine surgery

JJ Rasouli, J Shao, S Neifert, WN Gibbs… - Global Spine …, 2021 - journals.sagepub.com
Study Design: Narrative review. Objectives: Artificial intelligence (AI) and machine learning
(ML) have emerged as disruptive technologies with the potential to drastically affect clinical …

Co-authorship network analysis in cardiovascular research utilizing machine learning (2009–2019)

A Higaki, T Uetani, S Ikeda, O Yamaguchi - International Journal of Medical …, 2020 - Elsevier
Background With the recent advances in computational science, machine-learning methods
have been increasingly used in medical research. Because such projects usually require …

The impact of AI and robotics on physical, social‐emotional and intellectual learning outcomes: An integrated analytical framework

SZ Salas‐Pilco - British Journal of Educational Technology, 2020 - Wiley Online Library
This qualitative study examines the use of artificial intelligence (AI) and robotics in learning
designs from the perspective of learning sciences. The literature on the topic indicates that …

A novel memcapacitive-synapse neuron: Bionic modeling, complex dynamics analysis and circuit implementation

J Mou, T Ma, S Banerjee… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
With the growing exploration of brain actions, memristive elements with biomimetic
properties are urgently needed to estimate the activities of biological synapses. Based on …

Risk predictions of surgical wound complications based on a machine learning algorithm: A systematic review

H Zhang, J Zhao, R Farzan… - International Wound …, 2024 - Wiley Online Library
Surgical wounds may arise due to harm inflicted upon soft tissue during surgical
intervention, and many complications and injuries may accompany them. These …