AIMC Topic: COVID-19

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Practical Approach for Evaluating Machine Learning Anomaly Detection Algorithms for Epidemic Early Warning Systems.

Studies in health technology and informatics
Anomaly detection methods in time series data can play a pivotal role in epidemic surveillance Early Warning Systems (EWS). Statistical and rules-based methods have been traditionally employed in such systems, but are challenged by data dynamics and ...

Automatic Annotation of Disposition Counts in News Articles.

Studies in health technology and informatics
News media aggregate and report disposition counts during crises: how many people are affected, suspected affected, have died, and have recovered or been recovered; and they tend to do so in a timely and trustworthy manner. We present and evaluate a ...

Artificial Intelligence Powered Audiomics: The Futuristic Biomarker in Pulmonary Medicine - A State-of-the-Art Review.

Studies in health technology and informatics
AI-driven "audiomics" leverages voice and respiratory sounds as non-invasive biomarkers to diagnose and manage pulmonary conditions, including COVID-19, tuberculosis, ILD, asthma, and COPD. By analyzing acoustic features, machine and deep learning en...

FLANDERS: Fast Learning COVID-19 Care System.

Studies in health technology and informatics
The COVID-19 pandemic highlighted the complexities of diagnosing and managing acute Respiratory Failure (RF). Early prediction of RF remains a key challenge, with no established tools currently available. This study developed a machine learning model...

Pros, Cons and Limits of AI in Public Health.

Studies in health technology and informatics
This paper explores the role of Artificial Intelligence (AI) in Public Health (PH), examining its benefits, challenges, and ethical considerations. AI has become an essential tool in healthcare, improving diagnosis, treatment, and health system manag...

Evaluating Generative AI in Mental Health: Systematic Review of Capabilities and Limitations.

JMIR mental health
BACKGROUND: The global shortage of mental health professionals, exacerbated by increasing mental health needs post COVID-19, has stimulated growing interest in leveraging large language models to address these challenges.

A machine-learning-integrated portable electrochemiluminescence sensing platform for the visualization and high-throughput immunoassays.

Talanta
Electrochemiluminescence (ECL)-based point-of-care testing (POCT) has the potential to facilitate the rapid identification of diseases, offering advantages such as high sensitivity, strong selectivity, and minimal background interference. However, as...

In-depth analysis of the risk factors for persistent severe acute respiratory syndrome coronavirus 2 infection and construction of predictive models: an exploratory research study.

BMC infectious diseases
BACKGROUND: Persistent severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection differs from long coronavirus disease (COVID-19) (acute symptoms ≥ 12 weeks post-clearance). The Omicron BA.5 variant has a shorter median clearance time (1...

The Role of Artificial Intelligence in Drug Discovery and Pharmaceutical Development: A Paradigm Shift in the History of Pharmaceutical Industries.

AAPS PharmSciTech
In today's world, with an increasing patient population, the need for medications is increasing rapidly. However, the current practice of drug development is time-consuming and requires a lot of investment by the pharmaceutical industries. Currently,...

Prediction models based on machine learning algorithms for COVID-19 severity risk.

BMC public health
BACKGROUND: The World Health Organization has highlighted the risk of Disease X, urging pandemic preparedness. Coronavirus disease 2019 (COVID-19) could be the first Disease X; therefore, understanding the epidemiological experiences of COVID-19 is c...