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Causal AI in healthcare: a black box revelation?

Artificial intelligence (AI) and machine learning have great potential to improve people’s lives. From supporting data analysis in research to providing more accurate and quicker diagnostic tools. But their interior workings are questioned by many and understood by few. New models are needed to solve current shortcomings and causal AI might be our way out. By offering a peek inside the black box, it creates opportunities to implement AI in high-risk settings such as healthcare. But how far along are we and where is this journey taking us?
The Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM) is a standardized framework designed by the Observational Health Data Sciences and Informatics (OHDSI) community. This open-science community aims to improve the quality of healthcare by providing guidelines for a more harmonized approach to data science.
Personalized healthcare is characterized by tailoring treatments to each individual patient’s needs. Despite evident benefits, implementing such a system is not straightforward. The ATHENA project consortium has successfully devised a set of building blocks to address the challenges associated. Both technological and governance tools were developed that can now be used on a larger scale to catalyze the transition towards personalized medicine and care.
While a vast majority of women experience vaginal yeast infections, research has fallen short in providing an effective treatment approach. However, hope has emerged recently with the development of new model systems that allow exploration of the complex vaginal environment. Organ-on-chip models enable researchers to examine the interactions between human cells and microbes in a more accurate manner, offering the potential for the development of new therapies.
Innovative Smart Contact Lens Developer Awarded €2.5M in Funding for Groundbreaking Ocular Health Technology
Antibiotic resistance is a major concern for humans and animals. Increasing pressure to move away from antibiotics has created space for new solutions for disease management. Animab’s oral monoclonal antibody platform is a promising alternative, effectively guarding against infection during a vulnerable period in an animal’s development.
The patient’s journey in a healthcare setting is influenced by factors beyond the mere medical aspects of the case. Local variations in care procedures among hospitals and caregivers enable benchmarking and adaptation of practices to optimize outcomes. For effective process modeling, it’s essential to collect data and extract insights. To optimize this process efficiently, collaborative efforts should explore alternative data sources and implement novel tools.
In December 2023, Azalea Vision announced the first test of their smart contact lens on a real person. This demonstration showcased the first functional prototype of their smart lens, known as the ALMA lens, which was developed by the company to address ocular disorders characterized by the inability to effectively filter light.
Similar to the growing use of large-scale scientific data to guide laboratory research, urban data presents significant potential for informed decision-making in city governance. Extensive data on waste collection, traffic, pollution, and various other facets of city management can be collected and analyzed to help policymakers identify challenges and develop prediction-based solutions. Thomas Van Oppens, Deputy Mayor of Leuven, underscores the importance of local collaboration in establishing such a data-driven growth model for city governance.
As a CDMO in the life science industry, Unitron has a focus on the development and manufacturing of “electronics-inside” medical devices and the associated regulatory trajectory. The journey from innovative ideas to successful products are often bumpy and filled with challenges. Having a good understanding of this process and managing it well will boost your chances of success.
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  • Regional News

Artificial intelligence (AI) and machine learning have great potential to improve people’s lives. From supporting data analysis in research to providing more accurate and quicker diagnostic tools. But their interior workings are questioned by many and understood by few. New models are needed to solve current shortcomings and causal AI might be our way out. By offering a peek inside the black box, it creates opportunities to implement AI in high-risk settings such as healthcare. But how far along are we and where is this journey taking us?
The Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM) is a standardized framework designed by the Observational Health Data Sciences and Informatics (OHDSI) community. This open-science community aims to improve the quality of healthcare by providing guidelines for a more harmonized approach to data science.
Personalized healthcare is characterized by tailoring treatments to each individual patient’s needs. Despite evident benefits, implementing such a system is not straightforward. The ATHENA project consortium has successfully devised a set of building blocks to address the challenges associated. Both technological and governance tools were developed that can now be used on a larger scale to catalyze the transition towards personalized medicine and care.
While a vast majority of women experience vaginal yeast infections, research has fallen short in providing an effective treatment approach. However, hope has emerged recently with the development of new model systems that allow exploration of the complex vaginal environment. Organ-on-chip models enable researchers to examine the interactions between human cells and microbes in a more accurate manner, offering the potential for the development of new therapies.
Innovative Smart Contact Lens Developer Awarded €2.5M in Funding for Groundbreaking Ocular Health Technology
Antibiotic resistance is a major concern for humans and animals. Increasing pressure to move away from antibiotics has created space for new solutions for disease management. Animab’s oral monoclonal antibody platform is a promising alternative, effectively guarding against infection during a vulnerable period in an animal’s development.
The patient’s journey in a healthcare setting is influenced by factors beyond the mere medical aspects of the case. Local variations in care procedures among hospitals and caregivers enable benchmarking and adaptation of practices to optimize outcomes. For effective process modeling, it’s essential to collect data and extract insights. To optimize this process efficiently, collaborative efforts should explore alternative data sources and implement novel tools.
In December 2023, Azalea Vision announced the first test of their smart contact lens on a real person. This demonstration showcased the first functional prototype of their smart lens, known as the ALMA lens, which was developed by the company to address ocular disorders characterized by the inability to effectively filter light.
Similar to the growing use of large-scale scientific data to guide laboratory research, urban data presents significant potential for informed decision-making in city governance. Extensive data on waste collection, traffic, pollution, and various other facets of city management can be collected and analyzed to help policymakers identify challenges and develop prediction-based solutions. Thomas Van Oppens, Deputy Mayor of Leuven, underscores the importance of local collaboration in establishing such a data-driven growth model for city governance.
As a CDMO in the life science industry, Unitron has a focus on the development and manufacturing of “electronics-inside” medical devices and the associated regulatory trajectory. The journey from innovative ideas to successful products are often bumpy and filled with challenges. Having a good understanding of this process and managing it well will boost your chances of success.