The Complete Guide to Using AI in the Healthcare Industry in Winston Salem in 2025

Winston‑Salem is emerging as a practical hub for AI in healthcare in 2025 thanks to Wake Forest's Center for Artificial Intelligence Research - home to a dozen-plus projects that span ear‑drum diagnostics to AI models that predict breast‑cancer recurrence - and an Innovation Quarter that's welcoming diagnostics leaders to speed digital pathology into clinics.

Local momentum is anchored by translational units like the Center for Healthcare Innovation and the RegenMed Hub, which attracted companies such as Epredia and Aiforia to pilot AI‑driven imaging and clinical trials (Wake Forest Center for Artificial Intelligence Research, RegenMed Hub diagnostics program).

That mix of hospital access, industry partners, and training options makes Winston‑Salem a smart place for clinicians and staff to gain practical AI skills - courses like Nucamp's 15‑week AI Essentials for Work teach prompt writing and workplace AI fundamentals to help move lab breakthroughs into everyday care (Nucamp AI Essentials for Work bootcamp (15-week) - registration).

AI development requires a village.

Core AI technologies driving change in Winston‑Salem healthcare are familiar but powerful: machine learning (ML) for spotting patterns and predicting outcomes, deep learning and computer vision for scanning medical images, and natural language processing (NLP) - including large language models - for understanding and generating clinical text; together these tools form the backbone of systems that can speed diagnosis, personalize treatment, and streamline workflows (Overview of machine learning, deep learning, and NLP in healthcare).

The Internet of Medical Things (IoMT) and connected devices feed ML models with continuous data, while robotic process automation and workflow‑focused AI cut manual tasks so clinicians focus on care; Coursera's roundup of ML in health care lays out how these pieces fit into imaging, remote monitoring, and trial design (Machine learning, IoMT, and medical imaging in healthcare (Coursera)).

Locally, generative‑AI and documentation tools - such as Nuance DAX Copilot for clinical notes - illustrate how NLP can shave hours from charting, freeing clinicians the way a second set of eyes can quietly scan thousands of slides overnight to flag the few that matter (Nuance DAX Copilot clinical documentation automation example).

Today in Winston‑Salem the clearest, most tangible AI wins are already happening inside lung‑care pathways: Wake Forest Baptist and Atrium Health are using Optellum's FDA‑cleared Virtual Nodule Clinic to score pulmonary nodules, sort patients into high/intermediate/low risk, and guide which nodules need biopsy versus safe surveillance - an approach trained on more than 70,000 CT scans that helps catch cancers earlier when five‑year survival can jump from about 20% for late‑stage disease to as high as 90% for small, early tumors (Wake Forest Baptist AI and robotics lung cancer news release, Optellum Virtual Nodule Clinic case study).

Those image‑based predictions are being paired with robotic bronchoscopy to reach tiny, hard‑to‑access nodules and get better samples, while local research and recruitment hubs - see Atrium's Be Involved trials portal - are building pipelines that let AI flag candidates for novel therapies and earlier interventions (Atrium Health Be Involved clinical trials portal).

The result: fewer unnecessary biopsies, faster triage to treatment, and a practical workflow in which AI acts like a vigilant screening partner - quietly prioritizing the handful of scans that matter from the hundreds clinicians review each month.

“The exciting part of this artificial intelligence lung cancer prediction tool is that it enhances our decision making, helping doctors intervene sooner and treat more lung cancers at an earlier stage.”

Winston‑Salem's AI ecosystem is anchored by Wake Forest's Center for Artificial Intelligence Research (CAIR), which combines cutting‑edge projects (from interpretable weakly supervised models for breast histopathology to AI systems that aim to reduce alarm fatigue) with hands‑on education like the “AI for Future Clinicians” workshops at the Bowman Grey Center for Medical Education; learn more about CAIR's mission, awards, and internships on their site (Wake Forest CAIR research and education).

Cross‑center collaborations are accelerating translation - a recent CTSI announcement highlights a Joint Pilot Program launch (Aug. 28, 2025) with a $50,000 grant opportunity and a keynote by Dr. Sina Farsiu that ties vision research to clinical AI pilots (CTSI/CAIR Joint Pilot Program announcement).

Undergraduates aren't left on the sidelines: Wake Forest's URECA center funnels students into paid summer fellowships (for example, a 10‑week Wake Forest Research Fellowship with stipend and housing), creating a steady pipeline of talent who can staff local trials, internships, and startup partnerships (Wake Forest URECA undergraduate research opportunities).

The result is a practical, layered training and research network - tangible funding, student pipelines, and regular workshops - that turns lab ideas into hospital pilots faster than many mid‑sized cities can muster.

Adopting clinical AI in North Carolina has produced concrete, measurable wins that matter for Winston‑Salem hospitals weighing investment: Duke Health's Sepsis Watch program - an Epic‑integrated predictive analytics rollout - cut sepsis mortality by 31%, raised screening accuracy to 93%, and lowered false sepsis diagnoses by 62%, a reminder that better models can sharply reduce wasted alerts (Duke Health Sepsis Watch case study).

Other real‑world deployments back this up: UC San Diego's COMPOSER tool was linked to a 17% drop in in‑hospital sepsis deaths and less organ injury, while Johns Hopkins‑derived early‑warning systems have shown patients were identified hours sooner - nearly six hours in some studies - translating to dramatically earlier treatment and better outcomes (UCSD COMPOSER study, Johns Hopkins early‑warning results).

These programs also illustrate a practical lesson for Winston‑Salem: accuracy plus clinician responsiveness - not just alerts - drive impact, meaning measurable benefits can include fewer deaths, shorter stays, less organ damage, and fewer unnecessary tests when AI is carefully integrated into workflows.

“EMRAM recertification helped us optimize our EMR, improving our patient care and the experience of our clinical team.” - Dr. Eugenia McPeek Hinz, Duke Health

Winston‑Salem health systems must navigate a fast‑shifting policy landscape in 2025 where federal priorities and active state lawmaking intersect: the White House's “Winning the Race” AI Action Plan pushes a deregulatory, innovation‑first agenda while flagging that federal funding could be limited for states deemed to have “burdensome AI regulations,” a development that could directly affect North Carolina hospitals seeking pilot grants or federal research dollars (Analysis of the White House “Winning the Race” AI Action Plan and implications for health care funding).

At the same time, state activity is intense - dozens of bills this year target chatbot disclosures, limits on using AI as the sole basis for clinical or utilization decisions, and requirements for provider review and transparency - so local compliance programs must bridge federal signals and patchwork state rules, as tracked in Manatt's health AI policy roundup (Manatt health AI policy tracker for state health AI laws).

Practically, this means Winston‑Salem leaders should strengthen data governance, patient disclosure practices, and clinician oversight for diagnostic and documentation tools, because regulators are focusing on data quality, bias, and when AI must yield to a licensed professional; HealthTech's 2025 trends note that rising regulation will accompany broader adoption, so prepare governance when piloting ambient listening, RAG‑backed chatbots, or imaging algorithms (HealthTech 2025 AI trends overview for healthcare).

The takeaway: balancing innovation and patient safety is no abstract exercise - policy choices can influence federal funding, vendor selection, and the legal exposure of hospitals deploying AI tools.

“New policy and guidance are needed to ensure that they [AI-enabled health care tools] are designed, developed and deployed in a manner that is ...”

Begin simply: pick one high‑value workflow (for Winston‑Salem that often means imaging triage or documentation) and design a tightly scoped pilot that returns measurable wins within weeks - for example, a Virtual Nodule Clinic‑style trial that flags missed follow‑ups so a care team can close the loop on the single patient who matters among hundreds.

Partner with local translational hubs to move fast: Wake Forest's Center for Artificial Intelligence Research can help translate models into clinical pilots, while the Center for Healthcare Innovation's LAUNCH incubator offers an application pathway and networking events to seed projects and teams (Wake Forest Center for Artificial Intelligence Research (CAIR) - clinical AI translation, LAUNCH incubator 2025 application and RFA - Wake Forest Center for Healthcare Innovation).

Build governance from day one - document data sources, clinician review rules, and patient disclosure practices drawn from statewide debate and reporting on AI use in North Carolina - so pilots meet both ethical expectations and practical oversight needs (North Carolina Health News: How North Carolina providers are using AI in healthcare - examples and policy context).

Start with a minimum viable integration, measure clinical and workflow outcomes, iterate with clinicians, and use local grant and incubator opportunities to scale the solution into routine care; this stepwise loop keeps risk low while delivering visible, early wins.

“Not only do I truly believe that AI can really improve health care and health, I also believe we need AI to improve health care and improve health,” Silcox said.

Local leaders weighing AI investments in Winston‑Salem should see the numbers and the jobs story together: the U.S. AI medical diagnostics market is already valued at about $790 million in 2025 and - if current trends hold - could expand toward $4.29 billion by 2034, while overall healthcare spending is accelerating (an estimated 8% cost trend in 2025), pressure that pushes hospitals to hunt for efficiencies (U.S. AI medical diagnostics market 2025 report by CorelineSoft, Healthcare trends and five defining trends reshaping healthcare in 2025 - WNS).

Those dollars are already translating into concrete savings - WNS profiles an AI‑driven revenue‑cycle example that cut costs ~30% and lifted productivity ~40% - and that creates local demand for hybrid skill sets: clinical informatics, data engineers and validation specialists, AI‑assurance auditors, RCM operators who can work with agentic workflows, and clinicians trained to supervise generative‑AI documentation tools; at the same time, frontline roles like transcription and basic billing face disruption unless staff retool (Nucamp AI Essentials for Work - training to adapt healthcare jobs for AI).

For anyone plotting a career pivot, the practical takeaway is simple: combine clinical domain knowledge with data governance, model validation, or workflow integration skills and Winston‑Salem's translational hubs and health systems will likely have openings as tools move from pilot to practice - imagine a single AI triage tool shifting hundreds of administrative hours into a handful of new, higher‑value roles.

“AI is no longer just an assistant. It's at the heart of medical imaging, and we're constantly evolving to advance AI and support the future of precision medicine.”

Practitioners and innovators in Winston‑Salem can tap a dense, practical events ecosystem to learn, network, and pilot AI projects: bookmark the NC Biotech events calendar to find monthly meetups and funding workshops, join the Techstars Startup Weekend AI & Life Sciences (Feb 28–Mar 2, 2025 at Sparq) for hands‑on team sprints, or plan to meet investors and 75+ startups at ConvergeSouth 2025 (Sep 4–5 at Wake Forest Biotech Place) where sessions on applied AI and go‑to‑market strategy are front and center (NCBiotech events calendar, ConvergeSouth 2025 at Wake Forest Biotech Place).

For clinicians and researchers focused on regenerative medicine, the 12th Annual Regenerative Medicine Essentials Course (June 10–12) - with a free Public Day on June 9 - combines technical briefs, an industry expo, and workforce pipelines that feed local trials and startups (RME Course & Public Day).

Local infrastructure amplifies these events: a 2,500‑square‑foot test bed in downtown Winston‑Salem hums with high‑powered microscopes and even an Epredia E1000 Dx slide scanner that can read up to 1,000 slides, giving startups and hospital teams a real place to prototype and validate devices and AI workflows before clinical pilots.

“The Regenerative Medicine Engine provides a complete ecosystem for companies to launch, test their products and set the stage for commercial success.”

Looking ahead, Winston‑Salem's path from lab to bedside is clear: beginners should pair practical, short‑course skillbuilding with local engagement - start by learning workplace‑focused prompt writing and AI workflows in a hands‑on course like Nucamp's 15‑week AI Essentials for Work (Nucamp AI Essentials for Work (15-week bootcamp)), then plug into the city's research engine at Wake Forest's Center for Artificial Intelligence Research to attend the “Artificial Intelligence in Action” seminars, join membership networks, and seek summer internships that turn coursework into real clinical experience (Wake Forest Center for Artificial Intelligence Research - AI in Action seminars & internships); at the same time, obtain or refresh clinical and technical grounding via local health‑science programs at Forsyth Tech so that AI skills meet real workflows (Forsyth Tech Health Sciences programs).

A practical starter project - scope a narrowly defined documentation or imaging triage pilot, measure time saved and clinician review rates, and iterate with CAIR mentors - follows CAIR's playbook of pairing research, education, and translational pilots (examples include maternal‑risk and breast‑recurrence projects) and keeps risk low while producing visible wins; in short, combine a short, applied bootcamp, local clinic or classroom experience, and active participation in Wake Forest's seminars and internships, and the abstract promise of AI becomes the concrete improvement patients notice in day‑to‑day care.

“We can make a difference because we know that segments of the population are negatively impacted by the current health system. Something is not working, so how can we make use of the power of artificial intelligence to help?” - Metin Nafi Gurcan, PhD, Director, Center for Artificial Intelligence Research