| 1 |
What is the primary function of AI in the medical imaging industry?
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To improve diagnostic accuracy and patient outcomes |
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The article emphasizes that AI technology in medical imaging has the potential to transform medical practice by materially improving productivity and patient outcomes. This implies that the main goal of AI in this context is to enhance the accuracy and efficiency of medical diagnoses through imaging, which in turn leads to better treatment decisions and improved patient health. |
From the Background section of the abstract:
"Artificial intelligence (AI) technology has the potential to transform medical practice within the medical imaging industry and materially improve productivity and patient outcomes."
This directly supports the idea that AI’s primary function in medical imaging is to improve diagnostic accuracy and patient outcomes rather than focusing on cost reduction, administrative tasks, marketing, or research alone. |
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| 2 |
Which of the following is a key benefit of AI in radiology noted in the article?
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Acts as a second medical opinion |
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While the article does not explicitly say “second medical opinion,” it highlights AI’s role in improving diagnostic accuracy and supporting healthcare professionals. Acting as a second opinion aligns with AI helping radiologists by providing additional insights, improving trust, and aiding decision-making, which is a central theme in enhancing AI acceptability. |
AI in radiology serves as a supportive tool that enhances diagnostic accuracy by providing healthcare professionals with additional insights—essentially acting like a second medical opinion—thereby helping radiologists make better decisions. |
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| 3 |
What does AI literacy refer to according to the article?
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Understanding and knowledge of AI technology |
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The article lists AI literacy as a key user factor influencing AI acceptability, meaning how well healthcare professionals understand and are knowledgeable about AI technology affects their willingness to adopt it. |
AI literacy means how well healthcare professionals understand and know about AI technology, which influences their acceptance and effective use of AI in medical imaging. |
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| 4 |
Which factor is NOT listed as influencing the acceptability of AI among healthcare professionals?
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The color of the AI machines |
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the color of the AI machines is not mentioned anywhere as a factor affecting AI acceptability. The physical appearance or color of the hardware does not impact the professional’s trust, workflow integration, or understanding of AI systems in a meaningful way according to the literature reviewed.
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From the Results section of the abstract:
"The literature has converged towards three overarching categories of factors underpinning AI acceptability including: user factors involving trust, system understanding, AI literacy, and technology receptiveness; system usage factors entailing value proposition, self-efficacy, burden, and workflow integration; and socio-organisational-cultural factors encompassing social influence, organisational readiness, ethicality, and perceived threat to professional identity."
No mention of color or physical appearance is included. |
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| 5 |
What role does social influence play in AI acceptability in healthcare according to the article?
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Affects healthcare professionals’ decisions to use AI |
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The article lists social influence as one of the socio-organisational-cultural factors that impact AI acceptability. This means that the opinions, attitudes, and behaviors of colleagues, leaders, and the broader professional community can shape whether healthcare professionals choose to adopt and use AI technologies. |
From the Results section of the abstract:
"The literature has converged towards three overarching categories of factors underpinning AI acceptability including: ... socio-organisational-cultural factors encompassing social influence, organisational readiness, ethicality, and perceived threat to professional identity."
This indicates that social influence is a key socio-organizational factor that affects healthcare professionals’ acceptance and decisions to use AI systems. |
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| 6 |
What is a perceived threat regarding AI usage in healthcare settings?
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Concerns about replacing healthcare professionals |
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The article mentions “perceived threat to professional identity” as one of the socio-organizational-cultural factors influencing AI acceptability.
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This refers to healthcare professionals’ fear or concern that AI might replace or diminish their roles, which can negatively affect their willingness to adopt AI technologies. |
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| 7 |
According to the article, what is essential for increasing AI acceptability among medical professionals?
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Designing human-centred AI systems |
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The article concludes that increasing AI acceptability among medical professionals requires more than just high algorithmic performance. It emphasizes the importance of human-centred AI designs that consider user accessibility, AI literacy levels, integration into clinical workflows, and the cultural, ethical, and safety norms specific to healthcare professions. |
refer from "Increasing AI acceptability among medical professionals will critically require designing human-centred AI systems which go beyond high algorithmic performance to consider accessibility to users with varying degrees of AI literacy, clinical workflow practices, the institutional and deployment context, and the cultural, ethical, and safety norms of healthcare professions." |
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| 8 |
What does the 'system usage' category of AI acceptability factors include according to the article?
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Factors like value proposition and integration with workflows |
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The article groups system usage factors as including elements such as the perceived value of AI, users’ self-efficacy in using it, the burden it imposes, and how well it integrates into existing clinical workflows. These factors affect how smoothly AI fits into daily medical practice and influence its acceptability.
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System usage factors refer to practical aspects like the benefits AI offers, how easy it is to use, the workload it creates, and how well it fits into existing clinical workflows, all of which affect whether healthcare professionals accept AI. |
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| 9 |
How does ethicality impact AI acceptability among healthcare professionals?
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Affects views on AI based on compatibility with professional values |
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The article lists ethicality as one of the socio-organisational-cultural factors influencing AI acceptability. This means healthcare professionals evaluate AI systems based on whether they align with their ethical standards and professional values, which affects their willingness to adopt AI.
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Ethicality influences healthcare professionals’ acceptance of AI based on how well the technology aligns with their professional values and ethical standards. |
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| 10 |
What methodological approach did the article emphasize for future AI acceptability studies?
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Considering user experience and system integration deeply |
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The article highlights that many studies overlook critical healthcare-specific factors like clinical workflow impact and human-AI interaction nuances. It suggests future research should adopt approaches that deeply consider user experience, system integration, and the unique context of healthcare professionals to better understand and improve AI acceptability. |
From the Results and Conclusion sections of the abstract:
"Numerous studies have overlooked a meaningful subset of these factors that are integral to the use of medical AI systems such as the impact on clinical workflow practices... This is attributable to reliance on theoretical frameworks or ad-hoc approaches which do not explicitly account for healthcare-specific factors... Increasing AI acceptability among medical professionals will critically require designing human-centred AI systems which go beyond high algorithmic performance to consider accessibility to users with varying degrees of AI literacy, clinical workflow practices, the institutional and deployment context, and the cultural, ethical, and safety norms of healthcare professions." |
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| 11 |
What is the primary objective of using human embryonic stem cells in treating Parkinson’s disease?
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To replace lost dopamine neurons. |
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The main therapeutic goal in Parkinson’s treatment with stem cells is cell replacement therapy targeting the neurons lost to the disease. |
Parkinson’s disease is characterized mainly by the loss of dopamine-producing neurons in the brain, particularly in the substantia nigra region. Human embryonic stem cells (hESCs) are used in therapies to replace these lost dopamine neurons and restore dopamine levels, which can improve motor function in patients. This approach aims to directly address the core problem in Parkinson’s rather than just promoting plasticity, neurogenesis, or cognitive function. |
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| 12 |
Which animal was used to test the STEM-PD product for safety and efficacy?
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Rats |
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1.A 39-week GLP (Good Laboratory Practice) safety study for toxicity, tumorigenicity, and biodistribution
2.A non-GLP efficacy study that showed the transplanted cells led to full functional recovery in a pre-clinical rat model of Parkinson’s disease
This confirms that rats were the chosen animal model for both safety and efficacy testing of the STEM-PD product before moving to human clinical trials. |
Main Idea Reference
“...no adverse effects were observed upon testing of the product in a 39-week rat GLP safety study... and a non-GLP efficacy study confirmed that the transplanted cells mediated full functional recovery in a pre-clinical rat model of PD.” |
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| 13 |
What was the duration of the preclinical safety study in rats mentioned in the article?
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9 months |
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The 39-week duration is clearly noted in the context of rat safety testing, which confirms the study lasted approximately 9 months. |
To convert 39 weeks into months:
- 39 weeks ÷ 4.33 weeks/month ≈ 9 months |
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| 14 |
What is the name of the clinical trial phase mentioned for STEM-PD?
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Phase I/IIa |
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The article clearly states:
“...supporting the first-in-human STEM-PD Phase I/IIa clinical trial along with the trial design.”
This combined phase indicates early-stage human testing, focusing on both safety (Phase I) and preliminary efficacy (Phase IIa). |
“...Phase I/IIa clinical trial... initiated in 2022.” |
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| 15 |
How is the STEM-PD product manufactured?
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Under GMP-compliant conditions |
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GMP stands for Good Manufacturing Practice, which ensures that products are consistently produced and controlled according to quality standards required for clinical use. |
“...manufactured under GMP and quality tested in vitro and in vivo to meet regulatory requirements.”
This confirms the process follows strict, regulated conditions suitable for human clinical trials.
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| 16 |
According to the article, what confirmed the safety of the STEM-PD product in rats?
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There were no adverse effects or tumor formation. |
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The article reports:
“Importantly, no adverse effects were observed upon testing of the product in a 39-week rat GLP safety study for toxicity, tumorigenicity, and biodistribution...”
This means the product was safe, with no tumor formation, no toxic effects, and no unsafe spread of cells in the rats. |
“...no adverse effects were observed... for toxicity, tumorigenicity, and biodistribution…”
This directly confirms safety in the preclinical rat study. |
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| 17 |
What key finding was noted in the efficacy study of STEM-PD in rats?
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Transplanted cells reversed motor deficits in rats. |
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The article states:
“...a non-GLP efficacy study confirmed that the transplanted cells mediated full functional recovery in a pre-clinical rat model of PD.”
This means the rats with Parkinson-like symptoms regained motor function after receiving the transplanted stem cell-derived dopamine neurons — a clear sign of reversal of motor deficits. |
“...full functional recovery in a pre-clinical rat model of PD.”
This indicates the therapy worked effectively, restoring motor function — the primary goal in Parkinson’s treatment. |
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| 18 |
What specific markers were used to assess the purity of the STEM-PD batch?
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GIRK2 and ALDH1A1 |
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While the excerpt you shared doesn't mention the specific markers directly, GIRK2 and ALDH1A1 are well-established markers of midbrain dopaminergic neurons, especially the subtype lost in Parkinson’s disease (A9 neurons). These markers are commonly used in stem-cell based PD therapies to confirm that the derived cells are the correct type — pure, mature, and dopaminergic. |
1.GIRK2 (G-protein-regulated inwardly rectifying potassium channel 2)
2.ALDH1A1 (Aldehyde dehydrogenase 1A1)
Both are used to verify cell identity and purity in preclinical and clinical-grade dopaminergic neuron batches. |
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| 19 |
What role do growth factors like FGF8b and SHH play in the manufacturing process of STEM-PD?
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They are used in cell patterning for specific neural fates. |
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In the context of producing dopaminergic neurons for Parkinson’s disease therapy, FGF8b (Fibroblast Growth Factor 8b) and SHH (Sonic Hedgehog) are critical morphogens used during the differentiation process. Their function is to guide or "pattern" pluripotent stem cells into becoming specific types of neurons, particularly midbrain dopaminergic neurons, which are the subtype lost in PD. |
These growth factors are essential tools in directed differentiation, not for maintaining pluripotency, inducing apoptosis, or being irrelevant. |
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| 20 |
What was a key outcome measured in the preclinical trials for efficacy in rats?
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Recovery of motor function |
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“...a non-GLP efficacy study confirmed that the transplanted cells mediated full functional recovery in a pre-clinical rat model of PD.”
This means the primary measure of success in the efficacy study was whether the rats recovered motor function, which is directly relevant to Parkinson’s disease — a disorder characterized by motor deficits due to the loss of dopamine neurons. |
“...full functional recovery in a pre-clinical rat model of PD.”
This confirms the focus was on reversing motor impairments, not cognitive ability, anxiety, or lifespan.
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