The Case for Understanding Interdisciplinary Relationships in Health Care

Warren, James R.; Warren, Jimmie S.

doi:10.31486/toj.22.0111

Cited by 7 publications

(3 citation statements)

References 21 publications

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“…Logistical difficulties in implementing AI systems in healthcare include barriers to adoption and the need for sociocultural or pathway changes [29]. All stakeholders, including healthcare professionals, computational biologists, and policymakers, are increasingly compelled to understand each other's domain in order to identify a solution [30][31][32][33][34][35].…”

Section: Explainable Ai In Healthcare: Applications and Challengesmentioning

confidence: 99%

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: Explainable Ai In Healthcare: Applications and Challengesmentioning

confidence: 99%

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

“…Multidisciplinary research can address the genetic, sociocultural, and public health aspects of increased homozygosity, enabling a more nuanced and comprehensive assessment of its effects on human populations. This approach can offer a more complete perspective on the genetic and societal factors influencing homozygosity and guide the development of effective interventions and policies [ 57 ].…”

Section: Reviewmentioning

confidence: 99%

The Impact of Increased Homozygosity on Human Fertility: A Comprehensive Review

Prem,

Muneshwar,

Agrawal

et al. 2023

Cureus

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This comprehensive review explores the multifaceted relationship between increased homozygosity and human fertility, delving into the genetic, ethical, cultural, and public health dimensions of this complex phenomenon. Homozygosity, characterized by identical alleles at specific gene loci, can result from consanguineous marriages, genetic drift, and population isolation. The review highlights key findings, including the heightened risk of recessive genetic disorders, the implications for immune system diversity, and the influence on complex traits and diseases. It underscores the critical role of genetic counseling in addressing these consequences, considering the ethical implications, and respecting cultural practices. The delicate balance between genetic diversity and cultural norms is emphasized, calling for increased awareness and community engagement. Looking ahead, the review suggests emerging technologies, longitudinal studies, and interdisciplinary research as crucial avenues for further exploration, with the ultimate goal of informing effective public health policies and interventions that safeguard genetic diversity and cultural traditions for future generations.

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“…[4][5][6]11] All stakeholders, including healthcare professionals, computational biologists, and policymakers, are increasingly compelled to understand each other's domain in order to innovate a solution. [12][13][14][15][16][17] Specialized conferences play a crucial role in fostering interdisciplinary interactions, serving as platforms where experts from diverse fields can come together to share their research, exchange ideas, and form collaborative partnerships. [18][19][20] Through such collaborative ventures may transparency and interpretability of AI systems be advanced in healthcare and computational biology arenas.…”

Section: Introductionmentioning

confidence: 99%

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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The Case for Understanding Interdisciplinary Relationships in Health Care

Cited by 7 publications

References 21 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 Impact of Increased Homozygosity on Human Fertility: A Comprehensive Review

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

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