Public Health

Comparative study of lipid nanoparticle-based mRNA vaccine bioprocess with machine learning and combinatorial artificial neural network-design of experiment approach.

To develop a combinatorial artificial-neural-network design-of-experiment (ANN-DOE) model, the effect of ionizable lipid, an ionizable lipid-to-cholesterol ratio, N/P ratio, flow rate ratio (FRR), and total flow rate (TFR) on the outcome responses of mRNA-LNP vaccine were evaluated using a definitive screening design (DSD) and machine learning (ML) algorithms. Particle size (PS), PDI, zeta potenti...

Prediction of atmospheric pollutants in urban environment based on coupled deep learning model and sensitivity analysis.

Accurate and efficient predictions of pollutants in the atmosphere provide a reliable basis for the scientific management of atmospheric pollution. This study develops a model that combines an attention mechanism, convolutional neural network (CNN), and long short-term memory (LSTM) unit to predict the O and PM levels in the atmosphere, as well as an air quality index (AQI). The prediction results...

Strengths and limitations of new artificial intelligence tool for rare disease epidemiology.

The recent paper by Kariampuzha et al. describes an exciting application of artificial intelligence to rare disease epidemiology. The authors' AI mode...

Design of ear-contactless stethoscope and improvement in the performance of deep learning based on CNN to classify the heart sound.

Cardiac-related disorders are rapidly growing throughout the world. Accurate classification of cardiovascular diseases is an important research topic ...

Using artificial intelligence to reduce orthopedic surgical site infection surveillance workload: Algorithm design, validation, and implementation in 4 Spanish hospitals.

BACKGROUND: Surgical site infection (SSI) surveillance is a labor-intensive endeavor. We present the design and validation of an algorithm for SSI det...

Utilization of Bioinorganic Nanodrugs and Nanomaterials for the Control of Infectious Diseases Using Deep Learning.

As one of the main causes of morbidity and mortality, viral infections have a major impact on the well-being and economics of every nation in the glob...

Coupling machine learning and epidemiological modelling to characterise optimal fungicide doses when fungicide resistance is partial or quantitative.

Increasing fungicide dose tends to lead to better short-term control of plant diseases. However, high doses select more rapidly for fungicide resistan...

An investigation into epidemiological situations of COVID-19 with fuzzy K-means and K-prototype clustering methods.

The ten countries with the highest population during the pandemic were analyzed for clustering based on the quantitative numbers of COVID-19 and polic...

Piloting an automated clinical trial eligibility surveillance and provider alert system based on artificial intelligence and standard data models.

BACKGROUND: To advance new therapies into clinical care, clinical trials must recruit enough participants. Yet, many trials fail to do so, leading to ...

Talk with ChatGPT About the Outbreak of Mpox in 2022: Reflections and Suggestions from AI Dimensions.

In the era of big data, generative artificial intelligence (AI) models are currently in a boom. The Chatbot Generative Pre-trained Transformer (ChatGP...

Leveraging deep learning to improve vaccine design.

Deep learning has led to incredible breakthroughs in areas of research, from self-driving vehicles to solutions, to formal mathematical proofs. In the...

Radar Human Activity Recognition with an Attention-Based Deep Learning Network.

Radar-based human activity recognition (HAR) provides a non-contact method for many scenarios, such as human-computer interaction, smart security, and...

Beyond diagnosis: is there a role for radiomics in prostate cancer management?

The role of imaging in pretreatment staging and management of prostate cancer (PCa) is constantly evolving. In the last decade, there has been an ever...

Measurement and Processing of Thermographic Data of Passing Persons for Epidemiological Purposes.

Non-contact temperature measurement of persons during an epidemic is the most preferred measurement option because of the safety of personnel and mini...

A Fusion-Assisted Multi-Stream Deep Learning and ESO-Controlled Newton-Raphson-Based Feature Selection Approach for Human Gait Recognition.

The performance of human gait recognition (HGR) is affected by the partial obstruction of the human body caused by the limited field of view in video ...

A deep-learning algorithm to classify skin lesions from mpox virus infection.

Undetected infection and delayed isolation of infected individuals are key factors driving the monkeypox virus (now termed mpox virus or MPXV) outbrea...

Automated Monkeypox Skin Lesion Detection Using Deep Learning and Transfer Learning Techniques.

The current outbreak of monkeypox (mpox) has become a major public health concern because of the quick spread of this disease across multiple countrie...

Optimizing non-pharmaceutical intervention strategies against COVID-19 using artificial intelligence.

One key task in the early fight against the COVID-19 pandemic was to plan non-pharmaceutical interventions to reduce the spread of the infection while...

Intelligent detection of citrus fruit pests using machine vision system and convolutional neural network through transfer learning technique.

Plant pests and diseases play a significant role in reducing the quality of agricultural products. As one of the most important plant pathogens, pests...

Using Haplotype-Based Artificial Intelligence to Evaluate SARS-CoV-2 Novel Variants and Mutations.

IMPORTANCE: Earlier detection of emerging novel SARS-COV-2 variants is important for public health surveillance of potential viral threats and for ear...