BACKGROUND: Alzheimer's disease (AD) is one of many common neurodegenerative diseases without ideal treatment, but early detection and intervention can prevent the disease progression.
BACKGROUND: Amnestic mild cognitive impairment (aMCI) is the most common preclinical stage of Alzheimer's disease (AD). A strategy to reduce the impact of AD is the early aMCI diagnosis and clinical intervention. Neuroimaging, neurobiological, and ge...
In this paper, we review state-of-the-art approaches that apply signal processing (SP) and machine learning (ML) to automate the detection of Alzheimer's disease (AD) and its prodromal stages. In the first part of the document, we describe the econom...
BACKGROUND: There is a need for more reliable diagnostic tools for the early detection of Alzheimer's disease (AD). This can be a challenge due to a number of factors and logistics making machine learning a viable option.
Journal of X-ray science and technology
Jan 1, 2021
BACKGROUND: Chest X-ray imaging has been proved as a powerful diagnostic method to detect and diagnose COVID-19 cases due to its easy accessibility, lower cost and rapid imaging time.
BACKGROUND: Opioid use disorder (OUD) affects an estimated 16 million people worldwide. The diagnosis of OUD is commonly delayed or missed altogether. We aimed to test the utility of machine learning in creating a prediction model and algorithm for e...
OBJECTIVES: Early prediction of sepsis is of utmost importance to provide optimal care at an early stage. This work aims to deploy soft-computing and machine learning techniques for early prediction of sepsis.
OBJECTIVES: Sepsis is caused by infection and subsequent overreaction of immune system and will severely threaten human life. The early prediction is important for the treatment of sepsis. This report aims to develop an early prediction method for se...
OBJECTIVES: Early detection of sepsis is critical in clinical practice since each hour of delayed treatment has been associated with an increase in mortality due to irreversible organ damage. This study aimed to develop an explainable artificial inte...
OBJECTIVES: As a life-threatening condition, sepsis is one of the major public health issues worldwide. Early prediction can improve sepsis outcomes with appropriate interventions. With the PhysioNet/Computing in Cardiology Challenge 2019, we aimed t...