AIMC Topic: Artificial Intelligence

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A decade of machine learning-based predictive models for human pharmacokinetics: Advances and challenges.

Drug discovery today
Traditionally, in vitro and in vivo methods are useful for estimating human pharmacokinetics (PK) parameters; however, it is impractical to perform these complex and expensive experiments on a large number of compounds. The integration of publicly av...

AI for the collective analysis of a massive number of genome sequences: various examples from the small genome of pandemic SARS-CoV-2 to the human genome.

Genes & genetic systems
In genetics and related fields, huge amounts of data, such as genome sequences, are accumulating, and the use of artificial intelligence (AI) suitable for big data analysis has become increasingly important. Unsupervised AI that can reveal novel know...

Development of deep learning models for microglia analyses in brain tissue using DeePathology™ STUDIO.

Journal of neuroscience methods
BACKGROUND: Interest in artificial intelligence-driven analysis of medical images has seen a steep increase in recent years. Thus, our paper aims to promote and facilitate the use of this state-of-the-art technology to fellow researchers and clinicia...

Detection of Baseline Emotion in Brow Lift Patients Using Artificial Intelligence.

Aesthetic plastic surgery
BACKGROUND: The widespread popularity of browlifts and blepharoplasties speaks directly to the importance that patients place on the periorbital region of the face. In literature, most esthetic outcomes are based on instinctive analysis of the esthet...

Artificial intelligence-based image analysis can predict outcome in high-grade serous carcinoma via histology alone.

Scientific reports
High-grade extrauterine serous carcinoma (HGSC) is an aggressive tumor with high rates of recurrence, frequent chemotherapy resistance, and overall 5-year survival of less than 50%. Beyond determining and confirming the diagnosis itself, pathologist ...

Deep learning in cancer diagnosis, prognosis and treatment selection.

Genome medicine
Deep learning is a subdiscipline of artificial intelligence that uses a machine learning technique called artificial neural networks to extract patterns and make predictions from large data sets. The increasing adoption of deep learning across health...

Explainable artificial intelligence for pharmacovigilance: What features are important when predicting adverse outcomes?

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Explainable Artificial Intelligence (XAI) has been identified as a viable method for determining the importance of features when making predictions using Machine Learning (ML) models. In this study, we created models that ta...

Artificial intelligence for pre-operative lymph node staging in colorectal cancer: a systematic review and meta-analysis.

BMC cancer
BACKGROUND: Artificial intelligence (AI) is increasingly being used in medical imaging analysis. We aimed to evaluate the diagnostic accuracy of AI models used for detection of lymph node metastasis on pre-operative staging imaging for colorectal can...