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Design of experiments and artificial neural networks as useful tools in the optimization of analytical procedure.

Polimery w medycynie
Developing the analytical procedure requires estimating what independent variables will be tested and at what levels. There are statistical models that enable the optimization of the process. They involve statistical analysis, which indicates the cru...

AI and Big Data approaches to addressing the opioid crisis: a scoping review protocol.

BMJ open
INTRODUCTION: This paper outlines the steps necessary to assess the latest developments in artificial intelligence (AI) as well as Big Data technologies and their relevance to the opioid crisis. Fatal opioid overdoses have risen to over 82 998 annual...

Larger and more instructable language models become less reliable.

Nature
The prevailing methods to make large language models more powerful and amenable have been based on continuous scaling up (that is, increasing their size, data volume and computational resources) and bespoke shaping up (including post-filtering, fine ...

How can quantum computing be applied in clinical trial design and optimization?

Trends in pharmacological sciences
Clinical trials are necessary for assessing the safety and efficacy of treatments. However, trial timelines are severely delayed with minimal success due to a multitude of factors, including imperfect trial site selection, cohort recruitment challeng...

Pilot study protocol evaluating the impact of telerobotics interactions with autistic children during a Denver intervention on communication skills using single-case experimental design.

BMJ open
INTRODUCTION: For several years, studies have been conducted on the contribution of social robots as an intervention tool for children with autism spectrum disorder (ASD). One of the early intervention models recommended by the French National Author...

Core Concepts in Pharmacoepidemiology: Principled Use of Artificial Intelligence and Machine Learning in Pharmacoepidemiology and Healthcare Research.

Pharmacoepidemiology and drug safety
Artificial intelligence (AI) and machine learning (ML) are important tools across many fields of health and medical research. Pharmacoepidemiologists can bring essential methodological rigor and study design expertise to the design and use of these t...

Optimising the production of PLGA nanoparticles by combining design of experiment and machine learning.

International journal of pharmaceutics
Poly(lactic-co-glycolic acid) (PLGA) is a widely used biodegradable polymer in drug delivery and nanoparticle (NP) formulation due to its controlled drug release properties and safety profiles. Among the methods available for NP production, nanopreci...

An evaluation of the performance of stopping rules in AI-aided screening for psychological meta-analytical research.

Research synthesis methods
Several AI-aided screening tools have emerged to tackle the ever-expanding body of literature. These tools employ active learning, where algorithms sort abstracts based on human feedback. However, researchers using these tools face a crucial dilemma:...

Artificial intelligence (AI) for paediatric fracture detection: a multireader multicase (MRMC) study protocol.

BMJ open
INTRODUCTION: Paediatric fractures are common but can be easily missed on radiography leading to potentially serious implications including long-term pain, disability and missed opportunities for safeguarding in cases of inflicted injury. Artificial ...

QUAIDE - Quality assessment of AI preclinical studies in diagnostic endoscopy.

Gut
Artificial intelligence (AI) holds significant potential for enhancing quality of gastrointestinal (GI) endoscopy, but the adoption of AI in clinical practice is hampered by the lack of rigorous standardisation and development methodology ensuring ge...