Browsing by Subject "Artificial intelligence (AI)"

Now showing 1 - 5 of 5
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    Artificial Intelligence–Generated Research in the Literature: Is It Real or Is It Fraud?
    (Mary Ann Liebert, 2023) Stone, Jennifer A. M.; Anesthesia, School of Medicine
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    Computer-aided detection for colorectal neoplasia in randomized and non-randomized studies
    (Thieme, 2024-04-23) Mori, Yuichi; Patel, Harsh K.; Repici, Alessandro; Rex, Douglas K.; Sharma, Prateek; Hassan, Cesare; Medicine, School of Medicine
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    Federated learning as a catalyst for digital healthcare innovations
    (Elsevier, 2024-07-12) Yang, Guang; Edwards, Brandon; Bakas, Spyridon; Dou, Qi; Xu, Daguang; Li, Xiaoxiao; Wang, Wanying; Pathology and Laboratory Medicine, School of Medicine
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    Machine Learning and Artificial Intelligence in Surgical Fields
    (Springer, 2020-12) Egert, Melissa; Steward, James E.; Sundaram, Chandru P.; Urology, School of Medicine
    Artificial intelligence (AI) and machine learning (ML) have the potential to improve multiple facets of medical practice, including diagnosis of disease, surgical training, clinical outcomes, and access to healthcare. There have been various applications of this technology to surgical fields. AI and ML have been used to evaluate a surgeon's technical skill. These technologies can detect instrument motion, recognize patterns in video recordings, and track the physical motion, eye movements, and cognitive function of the surgeon. These modalities also aid in the advancement of robotic surgical training. The da Vinci Standard Surgical System developed a recording and playback system to help trainees receive tactical feedback to acquire more precision when operating. ML has shown promise in recognizing and classifying complex patterns on diagnostic images and within pathologic tissue analysis. This allows for more accurate and efficient diagnosis and treatment. Artificial neural networks are able to analyze sets of symptoms in conjunction with labs, imaging, and exam findings to determine the likelihood of a diagnosis or outcome. Telemedicine is another use of ML and AI that uses technology such as voice recognition to deliver health care remotely. Limitations include the need for large data sets to program computers to create the algorithms. There is also the potential for misclassification of data points that do not follow the typical patterns learned by the machine. As more applications of AI and ML are developed for the surgical field, further studies are needed to determine feasibility, efficacy, and cost.
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    The Use of Artificial Intelligence in Writing Scientific Review Articles
    (Springer, 2024) Kacena, Melissa A.; Plotkin, Lilian I.; Fehrenbacher, Jill C.; Orthopaedic Surgery, School of Medicine
    Purpose of review: With the recent explosion in the use of artificial intelligence (AI) and specifically ChatGPT, we sought to determine whether ChatGPT could be used to assist in writing credible, peer-reviewed, scientific review articles. We also sought to assess, in a scientific study, the advantages and limitations of using ChatGPT for this purpose. To accomplish this, 3 topics of importance in musculoskeletal research were selected: (1) the intersection of Alzheimer's disease and bone; (2) the neural regulation of fracture healing; and (3) COVID-19 and musculoskeletal health. For each of these topics, 3 approaches to write manuscript drafts were undertaken: (1) human only; (2) ChatGPT only (AI-only); and (3) combination approach of #1 and #2 (AI-assisted). Articles were extensively fact checked and edited to ensure scientific quality, resulting in final manuscripts that were significantly different from the original drafts. Numerous parameters were measured throughout the process to quantitate advantages and disadvantages of approaches. Recent findings: Overall, use of AI decreased the time spent to write the review article, but required more extensive fact checking. With the AI-only approach, up to 70% of the references cited were found to be inaccurate. Interestingly, the AI-assisted approach resulted in the highest similarity indices suggesting a higher likelihood of plagiarism. Finally, although the technology is rapidly changing, at the time of study, ChatGPT 4.0 had a cutoff date of September 2021 rendering identification of recent articles impossible. Therefore, all literature published past the cutoff date was manually provided to ChatGPT, rendering approaches #2 and #3 identical for contemporary citations. As a result, for the COVID-19 and musculoskeletal health topic, approach #2 was abandoned midstream due to the extensive overlap with approach #3. The main objective of this scientific study was to see whether AI could be used in a scientifically appropriate manner to improve the scientific writing process. Indeed, AI reduced the time for writing but had significant inaccuracies. The latter necessitates that AI cannot currently be used alone but could be used with careful oversight by humans to assist in writing scientific review articles.