AIMC Topic: Humans

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Smart parallel automated cryo-electron tomography.

Nature methods
In situ cryo-electron tomography enables investigation of macromolecules in their native cellular environment. Samples have become more readily available owing to recent software and hardware advancements. Data collection, however, still requires an ...

Global Research on Pandemics or Epidemics and Mental Health: A Natural Language Processing Study.

Journal of epidemiology and global health
BACKGROUND: The global research on pandemics or epidemics and mental health has been growing exponentially recently, which cannot be integrated through traditional systematic review. Our study aims to systematically synthesize the evidence using natu...

Targeting Machine Learning and Artificial Intelligence Algorithms in Health Care to Reduce Bias and Improve Population Health.

The Milbank quarterly
Policy Points Artificial intelligence (AI) is disruptively innovating health care and surpassing our ability to define its boundaries and roles in health care and regulate its application in legal and ethical ways. Significant progress has been made ...

Recent progress in artificial intelligence and machine learning for novel diabetes mellitus medications development.

Current medical research and opinion
Diabetes mellitus, stemming from either insulin resistance or inadequate insulin secretion, represents a complex ailment that results in prolonged hyperglycemia and severe complications. Patients endure severe ramifications such as kidney disease, vi...

Quantitative Three-Dimensional Imaging Analysis of HfO Nanoparticles in Single Cells via Deep Learning Aided X-ray Nano-Computed Tomography.

ACS nano
It is crucial for understanding mechanisms of drug action to quantify the three-dimensional (3D) drug distribution within a single cell at nanoscale resolution. Yet it remains a great challenge due to limited lateral resolution, detection sensitiviti...

Differentially Private Client Selection and Resource Allocation in Federated Learning for Medical Applications Using Graph Neural Networks.

Sensors (Basel, Switzerland)
Federated learning (FL) has emerged as a pivotal paradigm for training machine learning models across decentralized devices while maintaining data privacy. In the healthcare domain, FL enables collaborative training among diverse medical devices and ...

Identification of Psychological Treatment Dropout Predictors Using Machine Learning Models on Italian Patients Living with Overweight and Obesity Ineligible for Bariatric Surgery.

Nutrients
According to the main international guidelines, patients with obesity and psychiatric/psychological disorders who cannot be addressed to surgery are recommended to follow a nutritional approach and a psychological treatment. A total of 94 patients (T...