Vertebral Columns Winter 2024

Page 23

BIG DATA

From 1the University of California Davis in Sacramento, California; 2The Ohio State University College of Medicine in Columbus, Ohio; and 3The Ohio State University College of Engineering in Columbus, Ohio.

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Preserving Privacy in Big Data Spine Surgery Research Exploring Federated Learning Solutions Hania Shahzad, MD1

In the dynamic landscape of spine surger y research, the burgeoning utilization of national databases and registries has endowed orthopedic spine surgeons w it h an unprecedented wealth of patient data. This influx of medical information, stemming from diverse diagnostic tools and integrated healthcare systems, forms the bedrock for informed decision-making in patient care. As treatment guidelines increasingly rely on patterns discerned from datasets, the accurate interpretation of these colossal data becomes imperative, inf luencing healthcare operations and patient outcomes. The surge in data and the need to reliably analyze the data has given rise to the fields of big data, data mining, machine learning, and predictive modeling.

What Are Big Data, Data Mining, and Machine Learning? Big dat a refers to ex tensive a nd intricate datasets that are so large they require sophisticated software for interpretation, originating from diverse sources such as social media and business t ransact ions, char-

isass.org

acterized by high volume, variety, a nd velocit y. 1 Big data a na ly t ics extracts valuable insights, patterns, a nd k now le dge. Dat a m i n i ng i s a cr ucia l process w it hin t his domain, where meaningful patterns and correlations in large datasets are determined w it hout t he need for disclosing information that is deemed to be pr ivate. 2 Mach i ne learning (ML), a subset of artificial intelligence (AI), employs algorithmic approaches that enable machines to solve complex problems without explicit programming in medicine. In spine surgery, ML holds substantial promise for tasks such as diagnosis and outcome prediction where it can identify high-risk scenarios, offering potential insights into complications and revisions. 3,4 The computational process and data-driven nature of ML mark a t ransformat ive era in leveraging technology for improved postoperative outcomes.

What Is Predictive Modeling? To combat rising healthcare costs and introduce value into the healthcare system, policymakers, surgeons,

Cole Veliky, BS2

Eugine Shin, BS3

Aylin Yener, PhD3

Safdar N Khan, MD1

Vertebral Columns

Winter 2024


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