Taylor & Francis

Recently, the Alliance for Artificial Intelligence in Healthcare (AAIH) published "The Lifecycle of an AI System in Healthcare", a whitepaper defining what healthcare is and provides guidelines on implementing artificial intelligence (AI) and machine learning (ML) in this setting.

In this episode of Talking Techniques, we speak with Oscar Rodriguez, a board member at AAIH and one of the authors of this whitepaper, to find out more about what the lifecycle of AI is, the importance of having guidelines when applying AI or ML in healthcare and what the future holds for this type of computer modeling.

Contents:

Intro: 00:00 - 00:45What are some of the ways that AI is used in healthcare? 00:45 - 5:04What are the current limitations of using AI in healthcare settings? 5:04 - 9:28The lifecycle of an AI system: 9:28 - 14:04How did you develop these guidelines for AI in healthcare? 14:04 - 17:28Summary of the guidelines from the white paper: 17:28 - 19:09Do you think some of these guidelines could be applicable to AI outside of healthcare? 19:09 - 19:53Why is it important to have guidelines like these for AI and machine learning in healthcare? 19:53 - 22:11Why did you decide to focus on COVID-19 case studies? 22:11 - 23:05How do you think the pandemic has changed the way AI is used in healthcare? 23:05 - 26:26What's next for AI? 26:26 - 30:03

Recently, the Alliance for Artificial Intelligence in Healthcare (AAIH) published "The Lifecycle of an AI System in Healthcare", a whitepaper defining what healthcare is and provides guidelines on implementing artificial intelligence (AI) and machine learning (ML) in this setting.

In this episode of Talking Techniques, we speak with Oscar Rodriguez, a board member at AAIH and one of the authors of this whitepaper, to find out more about what the lifecycle of AI is, the importance of having guidelines when applying AI or ML in healthcare and what the future holds for this type of computer modeling.

Contents:

Intro: 00:00 - 00:45What are some of the ways that AI is used in healthcare? 00:45 - 5:04What are the current limitations of using AI in healthcare settings? 5:04 - 9:28The lifecycle of an AI system: 9:28 - 14:04How did you develop these guidelines for AI in healthcare? 14:04 - 17:28Summary of the guidelines from the white paper: 17:28 - 19:09Do you think some of these guidelines could be applicable to AI outside of healthcare? 19:09 - 19:53Why is it important to have guidelines like these for AI and machine learning in healthcare? 19:53 - 22:11Why did you decide to focus on COVID-19 case studies? 22:11 - 23:05How do you think the pandemic has changed the way AI is used in healthcare? 23:05 - 26:26What's next for AI? 26:26 - 30:03

Welcome to our newest podcast series, Editor's Picks, where we'll round up the latest life science news from BioTechniques.

In this bitesize podcast, we've got everything from the history of cephalopods in neuroscience research to recent advancements against antibiotic-resistant bacteria.

Mitigation strategies for the biological matrix supply chain: an interview with Mark O'Dell by Taylor & Francis Group

In this episode, supported by Zymo Research, guest host Georgia Bickerton explores NGS data and how bioinformatic pipelines and workflows can be optimized to make NGS data more accessible. To do this she speaks with Jeffrey Bhasin, Director of Informatics at Zymo Research, who discusses the key issues of reproducibility in bioinformatics, the selection of methods available to analyze different datasets and to investigate different aspects of these data.

Listen today to discover the techniques available to help increase the portability and reproducibility of fine-tuned bioinformatics workflows and to streamline the application of these workflows. Bhasin also reveals how these 'workflow management' technologies can enable more global, collaborative approaches to bioinformatics workflow construction and begin to increase the automation and accessibility of bioinformatics workflows.

Contents:

Introduction: 00:00-00:55

How the rise of NGS has impacted the field of bioinformatics: 00:55-01:35

Issues of reproducibility in bioinformatics: 01:35-03:50

Using bioinformatics for different data types and different applications: 03:50-06:10

The impact of bioinformatics workflow management: 06:10-08:50

The future of NGS data analysis: 08:50-12:05

Busting overreliance on bioinformatics experts? 12:05-15:05

Closing remarks: 15:05-15:50

ADA assay development: a podcast interview with Lynn Kamen by Taylor & Francis Group

The key diagnostic and prognostic information locked away in cell-free nucleic acids (cfNAs) has become increasingly accessible due to developments in genetic and epigenetic profiling techniques. These advances have engendered the rise of liquid biopsy techniques, which capture and analyze cfNAs from samples such as blood, saliva, urine and feces, in diagnostics and basic disease research.

However, challenges remain in the detection and analysis of these nucleic acid fragments, in part due to their low abundance and fragile nature. In this episode, Ayla Maunighan-Peter, Epigenetics Product Specialist at Zymo research (CA, USA), details the utility of these molecules, the challenges associated with their development and implementation of liquid biopsies and their use in both basic research and diagnostic spaces.

For an insight into how cfNAs can be used to identify novel drug targets, impact diagnostics development and be used to help soothe the organ shortage crisis, listen today!

Contents:

Intro: 00:00-00:40What are cfNAs? 1:50-02:35The role of cfNAs in Liquid biopsy: 02:35-04:25Markers analyzed in cfNAs: 04:25-06:10Epigenetic analysis of cfNAs: 06:05-07:55Techniques for epigenetic analysis of cfNAs: 08:00-08:55Introducing fragmentomics: 08:55-11:05Challenges in the development of liquid biopsy: 11:05-14:40How is the field trying to adapt to these challenges? 14:40-16:10Applications of cfNAs in basic research: 16:10-17:30The most exciting findings concerning the role of cfNAs in disease: 17:30-20:05One thing to improve our understanding and use of cfNAs: 20:05-21:10Conclusions: 21:15-22:15 

The key diagnostic and prognostic information locked away in cell-free nucleic acids (cfNAs) has become increasingly accessible due to developments in genetic and epigenetic profiling techniques. These advances have engendered the rise of liquid biopsy techniques, which capture and analyze cfNAs from samples such as blood, saliva, urine and feces, in diagnostics and basic disease research.

However, challenges remain in the detection and analysis of these nucleic acid fragments, in part due to their low abundance and fragile nature. In this episode, Ayla Maunighan-Peter, Epigenetics Product Specialist at Zymo research (CA, USA), details the utility of these molecules, the challenges associated with their development and implementation of liquid biopsies and their use in both basic research and diagnostic spaces.

For an insight into how cfNAs can be used to identify novel drug targets, impact diagnostics development and be used to help soothe the organ shortage crisis, listen today!

Contents:

Intro: 00:00-00:40What are cfNAs? 1:50-02:35The role of cfNAs in Liquid biopsy: 02:35-04:25Markers analyzed in cfNAs: 04:25-06:10Epigenetic analysis of cfNAs: 06:05-07:55Techniques for epigenetic analysis of cfNAs: 08:00-08:55Introducing fragmentomics: 08:55-11:05 Challenges in the development of liquid biopsy: 11:05-14:40How is the field trying to adapt to these challenges? 14:40-16:10Applications of cfNAs in basic research: 16:10-17:30The most exciting findings concerning the role of cfNAs in disease: 17:30-20:05One thing to improve our understanding and use of cfNAs: 20:05-21:10Conclusions: 21:15-22:15 

In this Tech Blast episode, we discuss preclinical models of non-alcoholic fatty liver disease with Gareth Guenigault, Lead Scientist of Services at CN Bio (Cambridge, UK). Gareth provides an overview of non-alcoholic steatohepatitis (NASH) therapeutic landscape and explains how incorporating organ-on-a-chip models into drug discovery workflows can improve this landscape.

Get Gareth’s expert insight into the field and discover how to develop liver-on-a-chip NASH models, tips for analyzing the resultant data, and the future of organ-on-a-chip technologies.

Contents:

Introduction: 00:00–00:30

Pathology and prevalence of NASH: 00:30–01:50

Challenges faced when developing drugs for NASH: 01:50–03:40

An overview of organ-on-a-chip models: 03:40–05:05

Liver-on-a-chip models for NASH: 05:05–07:05

Incorporating organ-on-a-chip into drug discovery workflows: 07:05–08:45

Accessing liver-on-a-chip and NASH models: 08:45–09:45

The NASH-in-a-box workflow: 09:45–10:45

Gareth’s tips for analyzing the data: 10:45–12:15

The future of organ-on-a-chip technology: 12:15–13:55

FON-2021-1277 OCTalks by Taylor & Francis Group