AIMC Topic: Artificial Intelligence

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Auditing the AI auditors: A framework for evaluating fairness and bias in high stakes AI predictive models.

The American psychologist
Researchers, governments, ethics watchdogs, and the public are increasingly voicing concerns about unfairness and bias in artificial intelligence (AI)-based decision tools. Psychology's more-than-a-century of research on the measurement of psychologi...

The potential of artificial intelligence-based applications in kidney pathology.

Current opinion in nephrology and hypertension
PURPOSE OF REVIEW: The field of pathology is currently undergoing a significant transformation from traditional glass slides to a digital format dependent on whole slide imaging. Transitioning from glass to digital has opened the field to development...

m6A modification: recent advances, anticancer targeted drug discovery and beyond.

Molecular cancer
Abnormal N6-methyladenosine (m6A) modification is closely associated with the occurrence, development, progression and prognosis of cancer, and aberrant m6A regulators have been identified as novel anticancer drug targets. Both traditional medicine-r...

Protein-DNA/RNA interactions: Machine intelligence tools and approaches in the era of artificial intelligence and big data.

Proteomics
With the development of artificial intelligence (AI) technologies and the availability of large amounts of biological data, computational methods for proteomics have undergone a developmental process from traditional machine learning to deep learning...

Can Artificial Intelligence Improve the Energy Efficiency of Manufacturing Companies? Evidence from China.

International journal of environmental research and public health
Improving energy efficiency is an important way to achieve low-carbon economic development, a common goal of most nations. Based on the comprehensive survey data of enterprises above a designated size in Guangdong Province, this paper studies the imp...

A novel lifelong machine learning-based method to eliminate calibration drift in clinical prediction models.

Artificial intelligence in medicine
OBJECTIVE: Clinical prediction models (CPMs) constructed based on artificial intelligence have been proven to have positive impacts on clinical activities. However, the deterioration of CPM performance over time has rarely been studied. This paper pr...

Artificial Intelligence in Head and Neck Imaging.

Seminars in ultrasound, CT, and MR
Artificial intelligence (AI) can be applied to head and neck imaging to augment image quality and various clinical tasks including segmentation of tumor volumes, tumor characterization, tumor prognostication and treatment response, and prediction of ...

Brain Tumor Imaging: Applications of Artificial Intelligence.

Seminars in ultrasound, CT, and MR
Artificial intelligence has become a popular field of research with goals of integrating it into the clinical decision-making process. A growing number of predictive models are being employed utilizing machine learning that includes quantitative, com...