AJR. American journal of roentgenology
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The doctor-patient relationship has been evolving from benevolent paternalism to a more patient-centered relationship in the modern era. Although artificial intelligence (AI) has the potential to improve nearly every aspect of health care, many physicians are skeptical about integrating AI into their current medical practice. The purpose of this article is to explore what AI means for the doctor-patient relationship and for breast imaging radiologists. ⋯ The promise of AI is its potential to release physicians from tasks that are better performed by automation. AI may enhance our diagnostic accuracy to the point that we are able to refocus on the art of the doctor-patient relationship.
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AJR Am J Roentgenol · Jan 2019
ReviewPeering Into the Black Box of Artificial Intelligence: Evaluation Metrics of Machine Learning Methods.
Machine learning (ML) and artificial intelligence (AI) are rapidly becoming the most talked about and controversial topics in radiology and medicine. Over the past few years, the numbers of ML- or AI-focused studies in the literature have increased almost exponentially, and ML has become a hot topic at academic and industry conferences. However, despite the increased awareness of ML as a tool, many medical professionals have a poor understanding of how ML works and how to critically appraise studies and tools that are presented to us. Thus, we present a brief overview of ML, explain the metrics used in ML and how to interpret them, and explain some of the technical jargon associated with the field so that readers with a medical background and basic knowledge of statistics can feel more comfortable when examining ML applications. ⋯ Attention to sample size, overfitting, underfitting, cross validation, as well as a broad knowledge of the metrics of machine learning, can help those with little or no technical knowledge begin to assess machine learning studies. However, transparency in methods and sharing of algorithms is vital to allow clinicians to assess these tools themselves.
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AJR Am J Roentgenol · Jan 2019
Comparative StudyGadolinium-Based Blood Volume Mapping From MRI With Ultrashort TE Versus CT and SPECT for Predicting Postoperative Lung Function in Patients With Non-Small Cell Lung Cancer.
The purpose of this study is to directly compare the capability of gadolinium-based blood volume (BV) mapping from MRI (BV-MRI) with ultrashort TE (UTE) with that of CT and perfusion SPECT in predicting the postoperative lung function of patients with non-small cell lung cancer (NSCLC). ⋯ BV-MRI with UTE has the potential to predict the postoperative lung function of patients with NSCLC more accurately than qualitatively assessed CT and SPECT, and it can be considered to be at least as useful as quantitatively assessed CT.
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AJR Am J Roentgenol · Jan 2019
Multiparametric MRI Features and Pathologic Outcome of Wedge-Shaped Lesions in the Peripheral Zone on T2-Weighted Images of the Prostate.
This study investigates the multiparametric MRI (mpMRI) characteristics and pathologic outcome of wedge-shaped lesions observed on T2-weighted images. ⋯ This study shows that a greater percentage of wedge-shaped features are malignant than was previously thought. Of importance, mpMRI (specifically, ADC maps) can distinguish between malignant and benign wedge-shaped features.
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AJR Am J Roentgenol · Jan 2019
Impact of a Health Information Technology-Enabled Appropriate Use Criterion on Utilization of Emergency Department CT for Renal Colic.
The purpose of this study was to evaluate the impact of an appropriate use criterion (AUC) for renal colic based on local best practice, implemented as electronic clinical decision support (CDS), on the emergency department (ED) use of CT for patients with suspected nephrolithiasis. ⋯ Implementing an AUC based on local best practice as CDS may effectively curb potential imaging overuse in a subset of ED patients with renal colic unlikely to have a complicated course or alternative dangerous diagnosis.