AIMC Topic: Humans

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The Potential of AI and ChatGPT in Improving Agricultural Injury and Illness Surveillance Programming and Dissemination.

Journal of agromedicine
Generative Artificial Intelligence (AI) provides unprecedented opportunities to improve injury surveillance systems in many ways, including the curation and publication of information related to agricultural injuries and illnesses. This editorial exp...

Prediction of interactions between cell surface proteins by machine learning.

Proteins
Cells detect changes in their external environments or communicate with each other through proteins on their surfaces. These cell surface proteins form a complicated network of interactions in order to fulfill their functions. The interactions betwee...

Deep Learning and Geriatric Mental Health.

The American journal of geriatric psychiatry : official journal of the American Association for Geriatric Psychiatry
The goal of this overview is to help clinicians develop basic proficiency with the terminology of deep learning and understand its fundamentals and early applications. We describe what machine learning and deep learning represent and explain the unde...

Sensitivity Evaluation of Enveloped and Non-enveloped Viruses to Ethanol Using Machine Learning: A Systematic Review.

Food and environmental virology
Viral diseases are a severe public health issue worldwide. During the coronavirus pandemic, the use of alcohol-based sanitizers was recommended by WHO. Enveloped viruses are sensitive to ethanol, whereas non-enveloped viruses are considerably less se...

Deep learning-based whole-body characterization of prostate cancer lesions on [Ga]Ga-PSMA-11 PET/CT in patients with post-prostatectomy recurrence.

European journal of nuclear medicine and molecular imaging
PURPOSE: The automatic segmentation and detection of prostate cancer (PC) lesions throughout the body are extremely challenging due to the lesions' complexity and variability in appearance, shape, and location. In this study, we investigated the perf...

Machine and deep learning methods for clinical outcome prediction based on physiological data of COVID-19 patients: a scoping review.

International journal of medical informatics
INTRODUCTION: Since the beginning of the COVID-19 pandemic, numerous machine and deep learning (MDL) methods have been proposed in the literature to analyze patient physiological data. The objective of this review is to summarize various aspects of t...

The effect of deep learning-based lesion segmentation on failure load calculations of metastatic femurs using finite element analysis.

Bone
Bone ranks as the third most frequent tissue affected by cancer metastases, following the lung and liver. Bone metastases are often painful and may result in pathological fracture, which is a major cause of morbidity and mortality in cancer patients....

Intrinsic and extrinsic techniques for quantification uncertainty of an interpretable GRU deep learning model used to predict atmospheric total suspended particulates (TSP) in Zabol, Iran during the dusty period of 120-days wind.

Environmental pollution (Barking, Essex : 1987)
Total suspended particulates (TSP), as a key pollutant, is a serious threat for air quality, climate, ecosystems and human health. Therefore, measurements, prediction and forecasting of TSP concentrations are necessary to mitigate their negative effe...