HIV/AIDS

Graph neural network-based cell switching for energy optimization in ultra-dense heterogeneous networks.

The development of ultra-dense heterogeneous networks (HetNets) will cause a significant rise in energy consumption with large-scale base station (BS) deployments, requiring cellular networks to be more energy efficient to reduce operational expense and promote sustainability. Cell switching is an effective method to achieve the energy efficiency goals, but traditional heuristic cell switching alg...

GradFreeBits: Gradient-Free Bit Allocation for Mixed-Precision Neural Networks.

Quantized neural networks (QNNs) are among the main approaches for deploying deep neural networks on low-resource edge devices. Training QNNs using different levels of precision throughout the network (mixed-precision quantization) typically achieves superior trade-offs between performance and computational load. However, optimizing the different precision levels of QNNs can be complicated, as the...

Prediction of Equipment Effectiveness using Hybrid Moving Average-Adaptive Neuro Fuzzy Inference System (MA-ANFIS) for decision support in Bus Body Building Industry.

Managers are driven to accomplish significantly higher levels of operational performance due to the difficulty of today's dynamic production environme...

Considerations and Challenges for Real-World Deployment of an Acoustic-Based COVID-19 Screening System.

Coronavirus disease 2019 (COVID-19) has led to countless deaths and widespread global disruptions. Acoustic-based artificial intelligence (AI) tools c...

Decision Aids, Doorknob Moments, and Physician-Patient Solidarity in EDs.

Potential benefits of decision aids and technology, such as artificial intelligence, used at the bedside are many and significant. Like any tools, the...

A mechanics-based approach to realize high-force capacity electroadhesives for robots.

Materials with electroprogrammable stiffness and adhesion can enhance the performance of robotic systems, but achieving large changes in stiffness and...

Non-intrusive deep learning-based computational speech metrics with high-accuracy across a wide range of acoustic scenes.

Speech with high sound quality and little noise is central to many of our communication tools, including calls, video conferencing and hearing aids. W...

AI-Based Video Segmentation: Procedural Steps or Basic Maneuvers?

INTRODUCTION: Video-based review of surgical procedures has proven to be useful in training by enabling efficiency in the qualitative assessment of su...

Opportunistic soaring by birds suggests new opportunities for atmospheric energy harvesting by flying robots.

The use of flying robots (drones) is increasing rapidly, but their utility is limited by high power demand, low specific energy storage and poor gust ...

An optimistic firefly algorithm-based deep learning approach for sentiment analysis of COVID-19 tweets.

The unprecedented rise in the number of COVID-19 cases has drawn global attention, as it has caused an adverse impact on the lives of people all over ...

Musculoskeletal radiologist-level performance by using deep learning for detection of scaphoid fractures on conventional multi-view radiographs of hand and wrist.

OBJECTIVES: To assess how an artificial intelligence (AI) algorithm performs against five experienced musculoskeletal radiologists in diagnosing scaph...

P-ResUnet: Segmentation of brain tissue with Purified Residual Unet.

Brain tissue of Magnetic Resonance Imaging is precisely segmented and quantified, which aids in the diagnosis of neurological diseases such as epileps...

The Health Gym: synthetic health-related datasets for the development of reinforcement learning algorithms.

In recent years, the machine learning research community has benefited tremendously from the availability of openly accessible benchmark datasets. Cli...

Generative adversarial network based data augmentation for CNN based detection of Covid-19.

Covid-19 has been a global concern since 2019, crippling the world economy and health. Biological diagnostic tools have since been developed to identi...

Multiplexed high-throughput immune cell imaging reveals molecular health-associated phenotypes.

Phenotypic plasticity is essential to the immune system, yet the factors that shape it are not fully understood. Here, we comprehensively analyze immu...

Isotropic reconstruction for electron tomography with deep learning.

Cryogenic electron tomography (cryoET) allows visualization of cellular structures in situ. However, anisotropic resolution arising from the intrinsic...

In-sensor neural network for high energy efficiency analog-to-information conversion.

This work presents an on-chip analog-to-information conversion technique that utilizes analog hyper-dimensional computing based on reservoir-computing...

LIAF-Net: Leaky Integrate and Analog Fire Network for Lightweight and Efficient Spatiotemporal Information Processing.

Spiking neural networks (SNNs) based on the leaky integrate and fire (LIF) model have been applied to energy-efficient temporal and spatiotemporal pro...

Artificial intelligence and treatment algorithms in spine surgery.

Artificial intelligence (AI) is a set of theories and techniques in which machines are used to simulate human intelligence with complex computer progr...

Deep learning in acute vertigo diagnosis.

Recent advances in artificial intelligence are transforming healthcare and there are increasing efforts to apply these breakthroughs to the diagnosis ...