Impact of artificial intelligence in transforming the doctor–cancer patient relationship

Heudel, P.-E.; Crochet, H.; Blay, J.-Y.

doi:10.1016/j.esmorw.2024.100026

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2024

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Cited by 3 publications

References 42 publications

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Clouds on the horizon: clinical decision support systems, the control problem, and physician-patient dialogue

Kara

2024

Med Health Care and Philos

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Clouds on the horizon: clinical decision support systems, the control problem, and physician-patient dialogue

Kara

2024

Med Health Care and Philos

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Integrating AI and Human Expertise: Exploring the Role of Radiomics in Multidisciplinary Tumor Boards

Shahid,

Ali,

Hammad Khan

et al. 2024

ARO

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In the ever-evolving landscape of oncology, the integration of artificial intelligence (AI) with radiomics has transformed the decision-making processes within multidisciplinary tumor boards (MDTs). MDTs serve as forums where specialists collaboratively discuss and recommend comprehensive treatment plans for patients with cancer, considering various clinical perspectives. This narrative review explores the synergistic relationship between AI and radiomics in oncology decision-making. We discuss the fundamentals of AI-powered radiomics, its workflow, and the role of radiomic features. Moreover, we delve into the integration of AI in radiology, radiation oncology, and medical oncology, emphasizing its impact on MDT decision-making, treatment planning, and predicting treatment responses, prognosis, and disease progression. Furthermore, we highlight the role of machine learning algorithms and their impact on MDT decision-making. We discuss the challenges and future implications of AI-driven radiomics in MDTs, considering ethical, financial, and regulatory aspects. Finally, we emphasize the transformative potential of AI-powered radiomics in reshaping oncology decision-making, facilitating more personalized and effective treatment strategies within MDTs.

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Personalized Communication

Yadav,

Kaur

2024

Advances in Computational Intelligence and Robotics

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Efficient doctor-patient cooperation is essential for achieving favorable healthcare results. The study examines the capacity of AI-powered solutions to improve individualized communication between medical professionals and patients. AI can utilize sophisticated natural language processing and machine learning methods to examine patient data, preferences, and medical history in order to customize communication strategies. These tools facilitate enhanced appointment scheduling, individualized treatment programs, and proactive health monitoring. Furthermore, artificial intelligence (AI) enhances patient education and involvement, resulting in enhanced compliance with treatment plans and overall health results. By using artificial intelligence (AI) in healthcare communication, healthcare practitioners can enhance the delivery of patient-centered care and cultivate more robust doctor-patient relationships.

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Impact of artificial intelligence in transforming the doctor–cancer patient relationship

Cited by 3 publications

References 42 publications

Clouds on the horizon: clinical decision support systems, the control problem, and physician-patient dialogue

Clouds on the horizon: clinical decision support systems, the control problem, and physician-patient dialogue

Integrating AI and Human Expertise: Exploring the Role of Radiomics in Multidisciplinary Tumor Boards

Personalized Communication

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