Henry Ford Hospital

The 2021 landscape of FDA-approved artificial intelligence/machine learning-enabled medical devices: An analysis of the characteristics and intended use

Simeng Zhu, Marissa Gilbert, Indrin J. Chetty et al.

2022 · 119 Zit.

Computational pathology in 2030: a Delphi study forecasting the role of AI in pathology within the next decade

M. Álvaro Berbís, David S. McClintock, Andrey Bychkov et al.

2023 · 101 Zit.

Comparison of Natural Language Processing Rules-based and Machine-learning Systems to Identify Lumbar Spine Imaging Findings Related to Low Back Pain

Wang-Chiew Tan, Saeed Hassanpour, Patrick J. Heagerty et al.

2018 · 86 Zit.

Artificial Intelligence for the Orthopaedic Surgeon: An Overview of Potential Benefits, Limitations, and Clinical Applications

Eric C. Makhni, Sonya Makhni, Prem N. Ramkumar

2020 · 74 Zit.

A Bibliometric Analysis of the Rise of ChatGPT in Medical Research

Nikki M. Barrington, Nithin Gupta, Basel Musmar et al.

2023 · 67 Zit.

Neurocritical Care Outcomes, Research, and Technology

Katharina M. Busl, Thomas P. Bleck, Panayiotis N. Varelas

2019 · 44 Zit.

Using Natural Language Processing of Free-Text Radiology Reports to Identify Type 1 Modic Endplate Changes

Hannu Huhdanpaa, Wang-Chiew Tan, Sean D. Rundell et al.

2017 · 44 Zit.

Artificial Intelligence in Facial Plastic Surgery: A Review of Current Applications, Future Applications, and Ethical Considerations

Elizabeth Choi, Kyle W. Leonard, Japnam S. Jassal et al.

2023 · 35 Zit.

Treatment of Complex Tibial Plateau Fractures with the Ilizarov External Fixator

Rosemary Buckle, Robert Blake, J. Tracy Watson et al.

1993 · 31 Zit.

Predicting intra‐operative and postoperative consequential events using machine‐learning techniques in patients undergoing robot‐assisted partial nephrectomy: a Vattikuti Collective Quality Initiative database study

Mahendra Bhandari, Anubhav Reddy Nallabasannagari, Madhu Reddiboina et al.

2020 · 28 Zit.

Quantifying surgical complexity with machine learning: Looking beyond patient factors to improve surgical models

Alexander Van Esbroeck, Ilan Rubinfeld, Bruce L. Hall et al.

2014 · 25 Zit.

ChatGPT‐4 Generates More Accurate and Complete Responses to Common Patient Questions About Anterior Cruciate Ligament Reconstruction Than Google’s Search Engine

Michael A. Gaudiani, Joshua Castle, Muhammad J. Abbas et al.

2024 · 18 Zit.

Application of Artificial Intelligence to Patient-Targeted Health Information on Kidney Stone Disease

Reza Kianian, Matthew Carter, Ilana Finkelshtein et al.

2023 · 18 Zit.

“What Program Directors Think” V: Results of the 2019 Spring Survey of the Association of Program Directors in Radiology (APDR)

Anna Rozenshtein, Brent Griffith, Priscilla J. Slanetz et al.

2020 · 16 Zit.

Evaluation of ChatGPT for Patient Counseling in Kidney Stone Clinic: A Prospective Study

Mohamed Javid, Mahendra Bhandari, P. Parameshwari et al.

2024 · 16 Zit.