Artificial Intelligence in Medical Practice: The Question to the Answer?

By D. Miller, E. Brown. American Journal of Medicine, 2017

651 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Health Informatics, Radiology, Nuclear Medicine and Imaging

View Paper: https://www.semanticscholar.org/paper/54edd7b3067751539c655868a964d69fcd8abf97

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

In Health Informatics

In Radiology, Nuclear Medicine and Imaging

Citations in the corpus

Remote patient monitoring using artificial intelligence: Current state, applications, and challenges (2023, neutral): “Artificial intelligence (AI) algorithms have been employed to perform analysis of medical images and correlate symptoms and biomarkers from clinical data to characterize an illness and its prognosis (Miller & Brown, 2018; Schnyer et al., 2017).”
Artificial Intelligence and Entrepreneurship: Implications for Venture Creation in the Fourth Industrial Revolution (2020, background): “…medical science context this might involve applications that can recognize cancer at an earlier stage than human experts ( Leachman & Merlino, 2017; Miller & Brown, 2018 ) or new technology firms such as Atomwise (Agrawal et al., 2019) who use AI to predict the outcome of chemical interactions,…”
Artificial Intelligence for Mental Health and Mental Illnesses: An Overview (2019, background): “While AI technology is becoming more prevalent in medicine for physical health applications, the discipline of mental health has been slower to adopt AI [8, 22].”
Legal and Ethical Consideration in Artificial Intelligence in Healthcare: Who Takes Responsibility? (2022, background): “To fully achieve the potential of AI in healthcare, four major ethical issues must be addressed: (1) informed consent to use data, (2) safety and transparency, (3) algorithmic fairness and biases, and (4) data privacy are all important factors to consider (27).”
The Internet of Things: Impact and Implications for Health Care Delivery (2020, background): “The scientific applications of AI have proliferated, including image analysis, text recognition with natural language processing, drug activity design, and prediction of gene mutation expression [53].”
Artificial intelligence in medical imaging: threat or opportunity? Radiologists again at the forefront of innovation in medicine (2018, background): “, we say here radiologists) remain essential for medical practice, because ingenuity in medicine requires unique human characteristics [40, 68].”
Rethinking drug design in the artificial intelligence era (2019, background): “The questions of whether a compound is ‘active against a target’ or ‘toxic’ are much more complex and labelled with much greater difficulty and nuances 43–45 .”
Artificial Intelligence Versus Clinicians in Disease Diagnosis: Systematic Review (2019, background): “AI may optimize the care trajectory of patients with chronic disease, suggest precision therapies for complex illnesses, and reduce medical errors [1].”
The Application of Medical Artificial Intelligence Technology in Rural Areas of Developing Countries (2018, background): “In rural areas, there are very few doctors; therefore, they are unlikely to lose their jobs or have their compensation reduced in the foreseeable future.(10)”
The rise of artificial intelligence in healthcare applications (2020, background): “(EMRs) with the characterization and prognosis of the disease [1].”
Physician Confidence in Artificial Intelligence: An Online Mobile Survey (2018, methodology): “AI programs have been widely used in the manufacturing sector, the information-communications industry [4], and the medical field [5-7].”
Outlining the Design Space of Explainable Intelligent Systems for Medical Diagnosis (2019, background): “It provides various system-centric solutions, such as developing accountable and transparent algorithms [11,43], visualizing obscure features [12,49], and employing theories from cognitive psychology to explore effective explanations [28,29,32].”