Dr. Cheng-Mao Zhou | Artificial Intelligence | Best Researcher Award

Researcher | Central People’s Hospital of Zhanjiang | China

Dr. Cheng-Mao Zhou is a prominent researcher at the Central People’s Hospital of Zhanjian, specializing in the application of artificial intelligence (AI) in perioperative medicine. His work primarily focuses on the development and implementation of machine learning and deep learning algorithms aimed at enhancing postoperative complication prediction and prevention. Dr. Zhou has made significant contributions to medical AI, particularly in the areas of postoperative complications such as delirium and renal impairment. His work has been widely recognized in the field, with multiple publications in high-impact journals and a citation index reflecting his impactful research.

Profile

Scopus

Education

Dr. Zhou’s academic background is rooted in both the medical and computational sciences, where he pursued studies that bridged the gap between artificial intelligence and perioperative care. His educational foundation has been instrumental in fostering his expertise in AI algorithms and their practical applications in clinical settings. Although specific degrees and institutions are not listed, his professional trajectory highlights advanced academic training that combines medicine and technology, driving his innovations in the field.

Experience

Dr. Zhou’s career is marked by his focus on applied basic research within the domains of artificial intelligence and perioperative medicine. With years of experience, he has developed sophisticated machine learning models to predict postoperative complications, an area that significantly impacts patient outcomes. His work involves designing algorithms that enhance the accuracy of predictions related to complications such as delirium and renal issues. Dr. Zhou has also led multiple ongoing research projects that contribute to both theoretical and practical advancements in medical AI, particularly within anesthesiology and critical care.

Research Interests

Dr. Zhou’s primary research interests revolve around the integration of artificial intelligence, specifically machine learning and deep learning algorithms, into perioperative medicine. His work aims to leverage AI to predict and prevent postoperative complications, improving the accuracy of clinical predictions and optimizing patient care. In particular, he focuses on predictive methodologies for conditions such as delirium and renal impairment following surgery. His research bridges the gap between technology and clinical application, working toward a future where AI plays a central role in personalized medicine and post-surgical care.

Awards

Dr. Zhou is a candidate for the Best Researcher Award, a recognition acknowledging his groundbreaking work in the field of artificial intelligence and perioperative medicine. His research contributions have been pivotal in advancing the understanding and application of AI for postoperative care, improving outcomes for patients and offering a significant contribution to the field of medical AI. Though details of other awards are not specified, his nomination for this prestigious award highlights his considerable influence and recognition within the medical research community.

Publications

Dr. Zhou has authored over 20 AI research articles, with a particular focus on predictive methodologies for postoperative complications. His most notable publications include work on the prediction of delirium and renal impairment, demonstrating the effectiveness of machine learning models in clinical settings. Below is a selection of his key publications:

“A predictive model for post-thoracoscopic surgery pulmonary complications based on the PBNN algorithm”

• • Authors: Zhou, C.-M., Xue, Q., Li, H., Yang, J.-J., Zhu, Y.
  • Year: 2024
  • Citations: 0

“Artificial intelligence algorithms for predicting post-operative ileus after laparoscopic surgery”

• • Authors: Zhou, C.-M., Li, H., Xue, Q., Yang, J.-J., Zhu, Y.
  • Year: 2024
  • Citations: 3

“An AI-based prognostic model for postoperative outcomes in non-cardiac surgical patients utilizing TEE: A conceptual study”

• • Authors: Zhu, Y., Liang, R., Zhou, C.-M.
  • Year: 2024
  • Citations: 0

“Predicting early postoperative PONV using multiple machine-learning- and deep-learning-algorithms”

• • Authors: Zhou, C.-M., Wang, Y., Xue, Q., Yang, J.-J., Zhu, Y.
  • Year: 2023
  • Citations: 6

“Predicting postoperative gastric cancer prognosis based on inflammatory factors and machine learning technology”

• • Authors: Zhou, C.-M., Wang, Y., Yang, J.-J., Zhu, Y.
  • Year: 2023
  • Citations: 10

“A long duration of intraoperative hypotension is associated with postoperative delirium occurrence following thoracic and orthopedic surgery in elderly”

• • Authors: Duan, W., Zhou, C.-M., Yang, J.-J., Ma, D.-Q., Yang, J.-J.
  • Year: 2023
  • Citations: 19

“Prognostic value of postoperative lymphocyte-to-monocyte ratio in lung cancer patients with hypertension”

• • Authors: Yuan, M., Wang, P., Meng, R., Zhou, C., Liu, G.
  • Year: 2023
  • Citations: 0

“Differentiation of Bone Metastasis in Elderly Patients With Lung Adenocarcinoma Using Multiple Machine Learning Algorithms”

• • Authors: Zhou, C.-M., Wang, Y., Xue, Q., Zhu, Y.
  • Year: 2023
  • Citations: 5

“Non-linear relationship of gamma-glutamyl transpeptidase to lymphocyte count ratio with the recurrence of hepatocellular carcinoma with staging I–II: a retrospective cohort study”

• • Authors: Li, Z., Liang, L., Duan, W., Zhou, C., Yang, J.-J.
  • Year: 2022
  • Citations: 2

“Predicting difficult airway intubation in thyroid surgery using multiple machine learning and deep learning algorithms”

• • Authors: Zhou, C.-M., Wang, Y., Xue, Q., Yang, J.-J., Zhu, Y.
  • Year: 2022
  • Citations: 16

Conclusion:
Dr. Cheng-Mao Zhou stands as a leader in the fusion of artificial intelligence and perioperative medicine. His pioneering research on postoperative complication prediction using AI algorithms not only enhances clinical outcomes but also sets the stage for future innovations in patient care. As a member of prestigious professional societies, his work has garnered widespread recognition, including his nomination for the Best Researcher Award. Dr. Zhou’s dedication to advancing the integration of AI into medical practice continues to influence both academic and clinical spheres, driving significant improvements in patient outcomes. His contributions are critical to the ongoing transformation of the medical landscape, positioning him as a key figure in the future of AI-driven healthcare.