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Quality Control

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Artificial Intelligence Algorithm Qualification: A Quality by Design Approach to Apply Artificial Intelligence in Pharma.

PDA journal of pharmaceutical science and technology
Quality is defined by the American Society for Quality (ASQ) as "the totality of features and characteristics of a product or service that bears on its ability to satisfy given needs." Therefore, quality is applicable to processes that supply outcome...

Gas-phase volatilomic approaches for quality control of brewing hops based on simultaneous GC-MS-IMS and machine learning.

Analytical and bioanalytical chemistry
For the first time, a prototype HS-GC-MS-IMS dual-detection system is presented for the analysis of volatile organic compounds (VOCs) in fields of quality control of brewing hop. With a soft ionization and drift time-based ion separation in IMS and a...

Using human in vitro transcriptome analysis to build trustworthy machine learning models for prediction of animal drug toxicity.

Scientific reports
During the development of new drugs or compounds there is a requirement for preclinical trials, commonly involving animal tests, to ascertain the safety of the compound prior to human trials. Machine learning techniques could provide an in-silico alt...

Detecting modeling inconsistencies in SNOMED CT using a machine learning technique.

Methods (San Diego, Calif.)
SNOMED CT is a comprehensive and evolving clinical reference terminology that has been widely adopted as a common vocabulary to promote interoperability between Electronic Health Records. Owing to its importance in healthcare, quality assurance becom...

Flaws (and quality) in research today: can artificial intelligence intervene?

Systems biology in reproductive medicine
The existing flaws in both conducting and reporting of research have been outlined and criticized in the past. Weak research design, poor methodology, lack of fresh ideas and poor reporting are the main points to blame. Issues have been continually r...

Machine-learning-based quality control of contractility of cultured human-induced pluripotent stem-cell-derived cardiomyocytes.

Biochemical and biophysical research communications
The precise and early assessment of cardiotoxicity is fundamental to bring forward novel drug candidates to the pharmaceutical market and to avoid their withdrawal from the market. Recent preclinical studies have attempted to use human-induced plurip...

NormAE: Deep Adversarial Learning Model to Remove Batch Effects in Liquid Chromatography Mass Spectrometry-Based Metabolomics Data.

Analytical chemistry
Untargeted metabolomics based on liquid chromatography-mass spectrometry is affected by nonlinear batch effects, which cover up biological effects, result in nonreproducibility, and are difficult to be calibrate. In this study, we propose a novel dee...

Spatiotemporal Approaches for Quality Control and Error Correction of Atmospheric Data through Machine Learning.

Computational intelligence and neuroscience
We propose three quality control (QC) techniques using machine learning that depend on the type of input data used for training. These include QC based on time series of a single weather element, QC based on time series in conjunction with other weat...

Artificial intelligence in diagnostic imaging: impact on the radiography profession.

The British journal of radiology
The arrival of artificially intelligent systems into the domain of medical imaging has focused attention and sparked much debate on the role and responsibilities of the radiologist. However, discussion about the impact of such technology on the radio...

Utilizing Machine Learning for Image Quality Assessment for Reflectance Confocal Microscopy.

The Journal of investigative dermatology
In vivo reflectance confocal microscopy (RCM) enables clinicians to examine lesions' morphological and cytological information in epidermal and dermal layers while reducing the need for biopsies. As RCM is being adopted more widely, the workflow is e...