AIMC Topic: Humans

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Performance of a point-of-care ultrasound platform for artificial intelligence-enabled assessment of pulmonary B-lines.

Cardiovascular ultrasound
BACKGROUND: The incorporation of artificial intelligence (AI) into point-of-care ultrasound (POCUS) platforms has rapidly increased. The number of B-lines present on lung ultrasound (LUS) serve as a useful tool for the assessment of pulmonary congest...

Recommendations for Artificial Intelligence Application in Continued Process Verification: A Journey Toward the Challenges and Benefits of AI in the Biopharmaceutical Industry.

PDA journal of pharmaceutical science and technology
This review paper explores the transformative impact of Artificial Intelligence (AI) on Continued Process Verification (CPV) in the biopharmaceutical industry. Originating from the CPV of the Future project, the study investigates the challenges and ...

Harnessing machine learning for rational drug design.

Advances in pharmacology (San Diego, Calif.)
A crucial part of biomedical research is drug discovery, which aims to find and create innovative medical treatments for a range of illnesses. However, there are intrinsic obstacles to the traditional approach of discovering novel medications, includ...

Machine learning-based risk predictive models for diabetic kidney disease in type 2 diabetes mellitus patients: a systematic review and meta-analysis.

Frontiers in endocrinology
BACKGROUND: Machine learning (ML) models are being increasingly employed to predict the risk of developing and progressing diabetic kidney disease (DKD) in patients with type 2 diabetes mellitus (T2DM). However, the performance of these models still ...

Interpretable machine learning model for early morbidity risk prediction in patients with sepsis-induced coagulopathy: a multi-center study.

Frontiers in immunology
BACKGROUND: Sepsis-induced coagulopathy (SIC) is a complex condition characterized by systemic inflammation and coagulopathy. This study aimed to develop and validate a machine learning (ML) model to predict SIC risk in patients with sepsis.

Effects of psychological torture and cybertorture with emerging digital technologies under anti-torture legal obligations in China: A mixed methods research in risks and remedies.

International journal of law and psychiatry
International norms and domestic law-making and decision-making often underestimate the effects of psychological torture and the challenges posed by digital technologies like artificial intelligence, neurotechnology, and cybertechnology, such as cybe...

Emotion-RGC net: A novel approach for emotion recognition in social media using RoBERTa and Graph Neural Networks.

PloS one
Emotion recognition in social media is a challenging task due to the complex and unstructured nature of user-generated content. In this paper, we propose Emotion-RGC Net, a novel deep learning model that integrates RoBERTa, Graph Neural Networks (GNN...

Migrative armadillo optimization enabled a one-dimensional quantum convolutional neural network for supply chain demand forecasting.

PloS one
Demand forecasting is a quite challenging task, which is sensitive to several factors such as endogenous and exogenous parameters. In the context of supply chain management, demand forecasting aids to optimize the resources effectively. In recent yea...

Automated Von Willebrand Factor Multimer Image Analysis for Improved Diagnosis and Classification of Von Willebrand Disease.

International journal of laboratory hematology
INTRODUCTION: Von Willebrand factor (VWF) multimer analysis is essential for diagnosing and classifying von Willebrand disease (VWD) but requires expert interpretation and is subject to inter-rater variability. We developed an automated image analysi...