AIMC Topic: Clinical Decision-Making

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Mapping the Use of Artificial Intelligence-Based Image Analysis for Clinical Decision-Making in Dentistry: A Scoping Review.

Clinical and experimental dental research
OBJECTIVES: Artificial intelligence (AI) is an emerging field in dentistry. AI is gradually being integrated into dentistry to improve clinical dental practice. The aims of this scoping review were to investigate the application of AI in image analys...

[Investigation of the impact of the deep learning based CT fractional flow reserve on clinical decision-making and long-term prognosis in patients with obstructive coronary heart disease].

Zhonghua xin xue guan bing za zhi
To investigate the impact of the deep-learning-based CT fractional flow reserve (CT-FFR) on clinical decision-making and long-term prognosis in patients with obstructive coronary heart disease. In this single-center retrospective cohort study, cons...

Care to Explain? AI Explanation Types Differentially Impact Chest Radiograph Diagnostic Performance and Physician Trust in AI.

Radiology
Background It is unclear whether artificial intelligence (AI) explanations help or hurt radiologists and other physicians in AI-assisted radiologic diagnostic decision-making. Purpose To test whether the type of AI explanation and the correctness and...

[Not Available].

Recenti progressi in medicina
This study explores the potential use of ChatGPT, an AI-based language model, in assessing herbal-drug interactions (HDi) to enhance clinical decision-making. HDi can pose significant health risks by reducing drug efficacy or causing unwanted side ef...

Artificial intelligence enhances the management of esophageal squamous cell carcinoma in the precision oncology era.

World journal of gastroenterology
Esophageal squamous cell carcinoma (ESCC) is the most common histological type of esophageal cancer with a poor prognosis. Early diagnosis and prognosis assessment are crucial for improving the survival rate of ESCC patients. With the advancement of ...

Machine learning-based individualized survival prediction model for prognosis in osteosarcoma: Data from the SEER database.

Medicine
Patient outcomes of osteosarcoma vary because of tumor heterogeneity and treatment strategies. This study aimed to compare the performance of multiple machine learning (ML) models with the traditional Cox proportional hazards (CoxPH) model in predict...

[APPLICATIONS OF ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING IN REHABILITATION].

Harefuah
The use of artificial intelligence applications in medicine has been common in recent decades. Machine learning, a subfield of artificial intelligence, is a methodology that allows computers to learn from examples and draw conclusions about new data....

Moonshot. Long shot. Or sure shot. What needs to happen to realize the full potential of AI in the fertility sector?

Human reproduction (Oxford, England)
Quality healthcare requires two critical components: patients' best interests and best decisions to achieve that goal. The first goal is the lodestar, unchanged and unchanging over time. The second component is a more dynamic and rapidly changing par...