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, grou** 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 …

Advancing UAV security with artificial intelligence: A comprehensive survey of techniques and future directions

F Tlili, S Ayed, LC Fourati - Internet of Things, 2024 - Elsevier
Abstract Unmanned Aerial Vehicles (UAVs) have become an integral part of modern smart
cities and systems. However, the proliferation of UAVs has also brought a significant security …

[HTML][HTML] Human-in-the-loop machine learning: Reconceptualizing the role of the user in interactive approaches

O Gómez-Carmona, D Casado-Mansilla… - Internet of Things, 2024 - Elsevier
The rise of intelligent systems and smart spaces has opened up new opportunities for
human–machine collaborations. Interactive Machine Learning (IML) contribute to fostering …

A Single Channel-Based Neonatal Sleep-Wake Classification using Hjorth Parameters and Improved Gradient Boosting

M Arslan, M Mubeen, SF Abbasi, MS Khan… - arxiv preprint arxiv …, 2024 - arxiv.org
Sleep plays a crucial role in neonatal development. Monitoring the sleep patterns in
neonates in a Neonatal Intensive Care Unit (NICU) is imperative for understanding the …

MS-HNN: Multi-scale hierarchical neural network with squeeze and excitation block for neonatal sleep staging using a single-channel EEG

H Zhu, L Wang, N Shen, Y Wu, S Feng… - … on Neural Systems …, 2023 - ieeexplore.ieee.org
Most existing neonatal sleep staging appro-aches applied multiple EEG channels to obtain
good performance. However, it potentially increased the computational complexity and led …

EEG-based neonatal sleep stage classification using ensemble learning

SF Abbasi, H Jamil, W Chen - … Materials & Continua, 2021 - research.birmingham.ac.uk
Sleep stage classification can provide important information regarding neonatal brain
development and maturation. Visual annotation, using polysomnography (PSG), is …

A hybrid DCNN-SVM model for classifying neonatal sleep and wake states based on facial expressions in video

M Awais, X Long, B Yin, SF Abbasi… - IEEE Journal of …, 2021 - ieeexplore.ieee.org
Sleep is a natural phenomenon controlled by the central nervous system. The sleep-wake
pattern, which functions as an essential indicator of neurophysiological organization in the …

A convolutional neural network-based decision support system for neonatal quiet sleep detection

SF Abbasi, QH Abbasi, F Saeed… - Mathematical …, 2023 - research.birmingham.ac.uk
Sleep plays an important role in neonatal brain and physical development, making its
detection and characterization important for assessing early-stage development. In this …

Auto-adaptive multilayer perceptron for univariate time series classification

FA Del Campo, MCG Neri, OOV Villegas… - Expert Systems with …, 2021 - Elsevier
Abstract Time Series Classification (TSC) is an intricate problem that has encountered
applications in various science fields. Accordingly, many researchers have presented …

Automatic neonatal sleep stage classification: a comparative study

SF Abbasi, A Abbas, I Ahmad, MS Alshehri, S Almakdi… - Heliyon, 2023 - cell.com
Sleep is an essential feature of living beings. For neonates, it is vital for their mental and
physical development. Sleep stage cycling is an important parameter to assess neonatal …