Related papers: Towards a Deep Learning Pain-Level Detection Deplo…
Pain management and severity detection are crucial for effective treatment, yet traditional self-reporting methods are subjective and may be unsuitable for non-verbal individuals (people with limited speaking skills). To address this…
This study presents a systematic machine-learning approach for classifying acute pain from raw electrophysiological signals. We address binary and ternary classification tasks, leveraging Power-In-Band (PIB) and signal coherence as…
Timely and rapid diagnoses are core to informing on optimum interventions that curb the spread of COVID-19. The use of medical images such as chest X-rays and CTs has been advocated to supplement the Reverse-Transcription Polymerase Chain…
From the original abstract: This thesis initially aims to study the pain assessment process from a clinical-theoretical perspective while exploring and examining existing automatic approaches. Building on this foundation, the primary…
Despite the rapid development of AI models in medical image analysis, their validation in real-world clinical settings remains limited. To address this, we introduce a generic framework designed for deploying image-based AI models in such…
Lung disease poses a substantial global health challenge, with pneumonia being a prevalent concern. This research focuses on leveraging deep learning techniques to detect and assess pneumonia, addressing two interconnected objectives.…
The COVID-19 pandemic has had a considerable impact on day-to-day life. Tackling the disease by providing the necessary resources to the affected is of paramount importance. However, estimation of the required resources is not a trivial…
Medical imaging plays a vital role in modern diagnostics; however, interpreting high-resolution radiological data remains time-consuming and susceptible to variability among clinicians. Traditional image processing techniques often lack the…
Current pain assessment within hospitals often relies on self-reporting or non-specific EKG vital signs. This system leaves critically ill, sedated, and cognitively impaired patients vulnerable to undertreated pain and opioid overuse.…
Purpose: Early detection and diagnosis of Covid-19 and accurate separation of patients with non-Covid-19 cases at the lowest cost and in the early stages of the disease are one of the main challenges in the epidemic of Covid-19. Concerning…
This paper presents a comprehensive review of recent advancements in image processing and deep learning techniques for pavement distress detection and classification, a critical aspect in modern pavement management systems. The conventional…
Assessing chronic pain behavior in mice is critical for preclinical studies. However, existing methods mostly rely on manual labeling of behavioral features, and humans lack a clear understanding of which behaviors best represent chronic…
A major shortcoming of medical practice is the lack of an objective measure of conscious level. Impairment of consciousness is common, e.g. following brain injury and seizures, which can also interfere with sensory processing and volitional…
The research titled "Early Detection of Post-COVID-19 Fatigue Syndrome using Deep Learning Models" addresses a pressing concern arising from the COVID-19 pandemic. Post-COVID-19 Fatigue Syndrome (PCFS) has become a significant health issue…
Manual identification and classification of pneumonia and COVID-19 infection is a cumbersome process that, if delayed can cause irreversible damage to the patient. We have compiled CT scan images from various sources, namely, from the China…
While Deep Learning (DL) is often considered the state-of-the art for Artificial Intelligence-based medical decision support, it remains sparsely implemented in clinical practice and poorly trusted by clinicians due to insufficient…
Novel coronavirus (COVID-19) outbreak, has raised a calamitous situation all over the world and has become one of the most acute and severe ailments in the past hundred years. The prevalence rate of COVID-19 is rapidly rising every day…
Pain monitoring is essential to the quality of care for patients undergoing a medical procedure with sedation. An automated mechanism for detecting pain could improve sedation dose titration. Previous studies on facial pain detection have…
This paper aims at providing researchers and engineering professionals with a practical and comprehensive deep learning based solution to detect construction equipment from the very first step of its development to the last one which is…
The detection of pilots' mental states is critical, as abnormal mental states have the potential to cause catastrophic accidents. This study demonstrates the feasibility of using deep learning techniques to classify different fatigue…