AIMC Topic: Reproducibility of Results

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[Determination of -nitrosodimethylamine in metformin hydrochloride and its preparations by high performance liquid chromatography-tandem mass spectrometry].

Se pu = Chinese journal of chromatography
A method was established for the determination of -nitrosodimethylamine (NDMA) in metformin hydrochloride active pharmaceutical ingredient (API) and preparation samples by high performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS). ...

The emergence of new trends in clinical laboratory diagnosis.

Saudi medical journal
Diagnostic processes typically rely on traditional and laborious methods, that are prone to human error, resulting in frequent misdiagnosis of diseases. Computational approaches are being increasingly used for more precise diagnosis of the clinical p...

The Performance of an Artificial Neural Network Model in Predicting the Early Distribution Kinetics of Propofol in Morbidly Obese and Lean Subjects.

Anesthesia and analgesia
BACKGROUND: Induction of anesthesia is a phase characterized by rapid changes in both drug concentration and drug effect. Conventional mammillary compartmental models are limited in their ability to accurately describe the early drug distribution kin...

Machine Learning Algorithm Validation: From Essentials to Advanced Applications and Implications for Regulatory Certification and Deployment.

Neuroimaging clinics of North America
The deployment of machine learning (ML) models in the health care domain can increase the speed and accuracy of diagnosis and improve treatment planning and patient care. Translating academic research to applications that are deployable in clinical s...

Pathomics in urology.

Current opinion in urology
PURPOSE OF REVIEW: Pathomics, the fusion of digitalized pathology and artificial intelligence, is currently changing the landscape of medical pathology and biologic disease classification. In this review, we give an overview of Pathomics and summariz...

The Development and Validation of a Machine Learning Model to Predict Bacteremia and Fungemia in Hospitalized Patients Using Electronic Health Record Data.

Critical care medicine
OBJECTIVES: Bacteremia and fungemia can cause life-threatening illness with high mortality rates, which increase with delays in antimicrobial therapy. The objective of this study is to develop machine learning models to predict blood culture results ...

Is Deep Learning On Par with Human Observers for Detection of Radiographically Visible and Occult Fractures of the Scaphoid?

Clinical orthopaedics and related research
BACKGROUND: Preliminary experience suggests that deep learning algorithms are nearly as good as humans in detecting common, displaced, and relatively obvious fractures (such as, distal radius or hip fractures). However, it is not known whether this a...

Artificial intelligence in medical imaging: A radiomic guide to precision phenotyping of cardiovascular disease.

Cardiovascular research
Rapid technological advances in non-invasive imaging, coupled with the availability of large data sets and the expansion of computational models and power, have revolutionized the role of imaging in medicine. Non-invasive imaging is the pillar of mod...

Bio-inspired gas sensing: boosting performance with sensor optimization guided by "machine learning".

Faraday discussions
The performance of existing gas sensors often degrades in field conditions because of the loss of measurement accuracy in the presence of interferences. Thus, new sensing approaches are required with improved sensor selectivity. We are developing a n...