Interdisciplinary Collaborations in Academia: Modeling the Roles of Perceived Contextual Norms and Motivation to Collaborate

Manata, Brian; Bozeman, Jessica; Boynton, Karen; Neal, Zachary

doi:10.1080/10510974.2023.2263922

Cited by 2 publications

(10 citation statements)

References 71 publications

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“…Nonetheless, collaborations across fields can foster innovative approaches to interpretability, such as leveraging human-centric design principles or drawing on theories of human cognition to inform model development. AI applications in healthcare demand transparency and explainability to address legal, ethical, and societal concerns, especially in clinical decision-making and patient care [72][73][74][75]. The integration of AI and computational biology into healthcare and research holds immense potential for accelerating discoveries, improving diagnostics, and enhancing patient care.…”

Section: Discussionmentioning

confidence: 99%

“…The future of XAI and computational biology in the context of Healthcare 5.0 will likely involve a careful balance between explainability and accuracy, with the ultimate goal being that of enhancing patient outcomes and upholding the essential elements of compassion, empathy, and ethical considerations that define the core of healthcare [100]. These advancements will likely have a profound impact on healthcare and biological research, leading to a deeper understanding of biological systems and improved patient outcomes [72][73][74][75][76].…”

Section: Discussionmentioning

confidence: 99%

“…Conferences are key for collaboration and innovation, uniting experts across fields, enabling knowledge exchange, and stimulating idea sharing [73][74][75]103]. They are vital for academic progress, research refinement, and fostering real-world impacts.…”

Section: Discussionmentioning

confidence: 99%

“…Collaborates with academia and healthcare providers to translate research into practice, addressing real-world problems and providing resources and expertise [73,74].…”

mentioning

confidence: 99%

“…Participates in conferences and workshops for knowledge sharing and idea generation, further amplifying cross-disciplinary interaction [74].…”

mentioning

confidence: 99%

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The Crucial Role of Interdisciplinary Conferences in Advancing Explainable AI in Healthcare

Patel,

Gu,

Esper

et al. 2024

BioMedInformatics

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As artificial intelligence (AI) integrates within the intersecting domains of healthcare and computational biology, developing interpretable models tailored to medical contexts is met with significant challenges. Explainable AI (XAI) is vital for fostering trust and enabling effective use of AI in healthcare, particularly in image-based specialties such as pathology and radiology where adjunctive AI solutions for diagnostic image analysis are increasingly utilized. Overcoming these challenges necessitates interdisciplinary collaboration, essential for advancing XAI to enhance patient care. This commentary underscores the critical role of interdisciplinary conferences in promoting the necessary cross-disciplinary exchange for XAI innovation. A literature review was conducted to identify key challenges, best practices, and case studies related to interdisciplinary collaboration for XAI in healthcare. The distinctive contributions of specialized conferences in fostering dialogue, driving innovation, and influencing research directions were scrutinized. Best practices and recommendations for fostering collaboration, organizing conferences, and achieving targeted XAI solutions were adapted from the literature. By enabling crucial collaborative junctures that drive XAI progress, interdisciplinary conferences integrate diverse insights to produce new ideas, identify knowledge gaps, crystallize solutions, and spur long-term partnerships that generate high-impact research. Thoughtful structuring of these events, such as including sessions focused on theoretical foundations, real-world applications, and standardized evaluation, along with ample networking opportunities, is key to directing varied expertise toward overcoming core challenges. Successful collaborations depend on building mutual understanding and respect, clear communication, defined roles, and a shared commitment to the ethical development of robust, interpretable models. Specialized conferences are essential to shape the future of explainable AI and computational biology, contributing to improved patient outcomes and healthcare innovations. Recognizing the catalytic power of this collaborative model is key to accelerating the innovation and implementation of interpretable AI in medicine.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

“…Collaborates with academia and healthcare providers to translate research into practice, addressing real-world problems and providing resources and expertise [73,74].…”

mentioning

confidence: 99%

“…Participates in conferences and workshops for knowledge sharing and idea generation, further amplifying cross-disciplinary interaction [74].…”

mentioning

confidence: 99%

See 3 more Smart Citations

The Crucial Role of Interdisciplinary Conferences in Advancing Explainable AI in Healthcare

Patel,

Gu,

Esper

et al. 2024

BioMedInformatics

View full text Add to dashboard Cite

show abstract

The Crucial Role of Interdisciplinary Conferences in Advancing Explainable AI in Healthcare

Patel,

Gu,

Esper

et al. 2024

Preprint

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Interdisciplinary conferences play a vital role in advancing explainable Artificial Intelligence (AI) within increasingly intersecting healthcare and computational biology arenas. Challenges result-ing from algorithmic bias and the necessity for domain-specific Explainable AI (XAI) techniques underscore the increasing significance of transparent and interpretable AI systems used in patient care. Collaborative efforts between clinicians, data scientists, and various stakeholders are nec-essary to innovate solutions tailored to healthcare needs. Specialized conferences may foster these interdisciplinary interactions, providing platforms for knowledge exchange, networking, and collaborative partnerships. The legal, ethical, and societal dimensions of medical AI advocate for an integrative approach that aligns technological advancements with patient-centered care val-ues. The role of specialized conferences is therefore essential for shaping future directions in ex-plainable AI and computational biology that contribute to improved patient outcomes and healthcare innovations.

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Interdisciplinary Collaborations in Academia: Modeling the Roles of Perceived Contextual Norms and Motivation to Collaborate

Abstract: Interdisciplinary collaborations in academia: Modeling the roles of perceived contextual norms and motivation to collaborate. In Communication Studies.

Cited by 2 publications

References 71 publications

The Crucial Role of Interdisciplinary Conferences in Advancing Explainable AI in Healthcare

The Crucial Role of Interdisciplinary Conferences in Advancing Explainable AI in Healthcare

The Crucial Role of Interdisciplinary Conferences in Advancing Explainable AI in Healthcare

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