Top 10 AI Prompts and Use Cases and in the Healthcare Industry in Palm Coast

Palm Coast is already seeing AI move from pilot to patient care: AdventHealth Palm Coast's new CathWorks platform - now used in roughly 80% of eligible Flagler County cases since its May 2024 launch - helps cardiologists pinpoint artery blockages without threading extra wires or relying on large doses of blood thinners, cutting invasiveness and speeding recovery (AdventHealth Palm Coast CathWorks report).

That clinical progress sits alongside Florida colleges expanding the talent pipeline - Palm Beach State College rolled out AI and medical imaging programs to meet demand - and local upskilling options like the 15-week AI Essentials for Work bootcamp, which teaches practical AI tools and prompt-writing for nontechnical professionals (Palm Beach State College AI and medical imaging programs; Nucamp AI Essentials for Work bootcamp registration).

Expect the Top 10 prompts and use cases ahead to connect these clinical wins to everyday workflows and training opportunities in Florida health systems.

Metric	Value
AdventHealth Palm Coast CathWorks cases	85
AdventHealth Palm Coast Parkway procedures	10
Usage since May 2024	~80% of eligible cases

“This technology helps us identify which blockages need to be treated more effectively. It's a big step forward in ensuring patients get the best possible care.” - Dr. Dean Abtahi

Methodology focused on real-world impact in Florida health systems, strong evidence, workflow readiness, and workforce feasibility: priority went to solutions already in patient care - like AdventHealth's CathWorks platform, which has been used in about 80% of eligible Flagler County cases since its May 2024 launch - because tools that reduce wires and high-dose blood thinners demonstrate tangible clinical benefit (CathWorks use in Flagler County - AdventHealth AI-driven heart care).

Candidates also needed backing from the peer-reviewed literature or comprehensive reviews to avoid hype, so we leaned on syntheses such as the open-access BMC review of AI's role in clinical practice to judge generalizability and safety considerations (BMC open-access review on AI in clinical practice).

Finally, interoperability and workflow fit - evidenced by tools already integrating with EHRs like Labcorp's AI-enhanced Test Finder - was required to ensure pilots could scale without breaking clinicians' day-to-day systems (Labcorp AI-enhanced Test Finder and EHR integration).

“This technology helps us identify which blockages need to be treated more effectively. It's a big step forward in ensuring patients get the best possible care.” - Dr. Dean Abtahi

CathWorks is reshaping cardiac care in Palm Coast by giving cardiologists physiology-grade insight from routine angiograms - no pressure wires, no drug stimulation - so teams can decide which lesions truly need treatment without extra invasiveness; AdventHealth reports the platform has been used in about 80% of eligible Flagler County cases since its May 2024 launch, cutting reliance on extra tools and high‑dose blood thinners and helping procedures run faster and with lower risk (AdventHealth Palm Coast's CathWorks rollout).

Built around the FFRangio approach, the CathWorks system combines AI and computational modeling to provide real‑time fractional flow reserve estimates across the coronary tree - think of skipping the tug of pressure wires and the rush of adenosine while still getting physiologic maps to target the most important segments (CathWorks FFRangio system).

Early local adoption - 85 cases at AdventHealth Palm Coast and 10 procedures at Palm Coast Parkway - shows how a wire‑free, drug‑free workflow can move from pilot to routine care and improve decision-making at the bedside.

Metric	Value
Usage since May 2024	~80% of eligible cases
AdventHealth Palm Coast cases	85
AdventHealth Palm Coast Parkway procedures	10

“This technology helps us identify which blockages need to be treated more effectively. It's a big step forward in ensuring patients get the best possible care.” - Dr. Dean Abtahi

Predictive analytics can turn routine clinic and EHR data into early-warning signals that matter in Palm Coast and across Florida - flagging patients at high risk for heart failure progression or readmission so teams can intervene before a bad day becomes an emergency visit.

Reviews show that integrating AI with EHRs improves cardiovascular risk prediction but requires local recalibration and careful validation: a comprehensive review of EHR‑based CVD models outlines gains from deep learning alongside pitfalls like geographic variability and data‑quality issues (comprehensive JAHA review on EHR and AI for cardiovascular risk prediction), while a focused literature synthesis of heart‑failure predictive models highlights both high-performing approaches and the importance of transparent reporting and external validation (systematic review of predictive analytics in heart failure).

On the ground, practical pilots in Palm Coast - think AI‑powered preventive monitoring that helps clinicians catch deterioration early - show how risk scores can trigger timely outreach and avoid costly ER visits (case study of AI-powered preventive monitoring in Palm Coast healthcare).

The takeaway: predictive tools can genuinely shift care from reactive to proactive, but only when models are transparently reported, locally validated, and embedded into workflows that make the next clinical step simple and immediate - turning alerts into appointments, not extra work.

Model	Reported Performance (AUROC)
BEHRT (transformer-based)	HF: 0.909
PREVENT	Men: 0.757; Women: 0.794
Pooled Cohort Equations (PCE)	0.713–0.818

Nuance's DAX Copilot brings ambient, generative AI into the clinical room to turn conversations into specialty‑specific draft notes that slot directly into Epic - a workflow win for busy Florida practices that need documentation to be fast, accurate, and EHR‑friendly; the integration with Epic's Haiku and Hyperspace means clinicians can capture encounters on the move and populate growing sets of structured fields automatically (DAX Copilot and Epic integration deep dive).

Real-world studies and vendor outcomes show why this matters: ambient voice is already relied on by roughly 85–90% of physicians and can cut documentation time by about 50% (roughly 6–7 minutes per visit), while health systems using the Copilot report measurable gains - one large system saw clinicians spend 24% less time on notes and see an average of 11.3 more patients per month, plus a 17% drop in after‑hours “pajama time” (Dragon Copilot outcomes and feature summary).

Peer‑reviewed evaluation reinforces productivity and engagement benefits when deployment includes training and oversight (Cohort study evaluating DAX Copilot's impact), and even Florida organizations like Orlando Health have highlighted platform security as a deployment advantage - together, these changes translate to clearer notes, faster billing, and, most tangibly, more face‑time with patients instead of screens.

Metric	Reported value
Physicians relying on ambient voice	85–90%
Average reduction in documentation time	~50% (≈6–7 minutes/encounter)
Reported reduction in note time (case study)	24%
Additional patients/month (case study)	11.3
Decrease in after-hours charting (“pajama time”)	17%

“Since we have implemented DAX Copilot, I have not left clinic with an open note... In one word, DAX Copilot is transformative.” - Dr. Patrick McGill

NVIDIA Clara's federated learning stack lets Florida health systems scale imaging AI without moving patient scans - training locally and sharing only partial model updates so hospitals can pool knowledge while keeping PHI on-site; the Clara Train SDK describes a server–client gRPC workflow, MMAR support for bring‑your‑own models, and real‑world parity (e.g., BRATS brain‑tumor experiments reaching Dice ≈0.82) that proves federation can match centralized quality (NVIDIA Clara federated learning overview).

Pairing federation with synthetic data generation further accelerates model buildout for rare cases and pediatric cohorts by creating labeled images without patient exposure - synthetic-first pipelines reduce annotation costs and help systems validate models on hybrid datasets before clinical use (Synthetic data for medical imaging: benefits and use cases).

For hospitals worried about leakage, NVIDIA FLARE and Clara provide practical protections - mutual authentication, SSL tokens, secure aggregation and even CUDA‑accelerated homomorphic encryption options - so a Palm Coast network could improve detection models across clinics

“without a single CT leaving the scanner room,”

then validate performance locally before deployment (NVIDIA FLARE: turning machine learning into federated learning).

The result: collaborative, privacy‑aware training that speeds development while keeping clinicians and regulators reassured.

Feature	Benefit
Partial model weight sharing	Preserves patient privacy; reduces risk of data inversion
MMAR & local training	Bring‑your‑own models; control over local compute and epochs
Secure transport & HE options	gRPC+SSL tokens and CUDA HE for encrypted federated XGBoost

For Palm Coast imaging teams, GE Healthcare's AIR Recon DL brings deep‑learning MRI reconstruction that meaningfully tightens the gap between image quality and patient comfort: the algorithm sharpens images by as much as 60% while cutting scan times up to 50%, which means fewer repeat sequences, faster throughput, and less time anxious patients spend inside the MR bore - turning a grueling 30‑minute slot into a high‑quality, five‑minute exam in the hands of experienced sites (GE Healthcare AIR Recon DL MRI reconstruction product page).

Those gains are already visible in case studies - Precision Imaging Center in Jacksonville, Florida reported roughly 50% less scan time for musculoskeletal work - and the platform's expansion to 3D sequences and the motion‑insensitive PROPELLER protocol makes it especially useful for pediatric, geriatric, and claustrophobic patients (MedImaging article on AIR Recon DL extensions and clinical impact).

Crucially for budget‑conscious Florida providers, AIR Recon DL can be deployed as an upgrade on many older GE scanners, effectively modernizing fleets without full replacement and helping sites reclaim schedule capacity - clinicians and managers can see the ROI in added time slots and fewer callbacks, not just prettier pictures.

Metric	Reported value
Image sharpness improvement	Up to 60%
Scan time reduction	Up to 50%
Patients scanned with AIR Recon DL (since launch)	Millions (≥2 million reported)
Compatibility	1.5T, 3.0T, 7.0T; available as upgrade for older scanners

“It's not just about doing a five minute knee exam, it's doing a high quality five minute knee exam.” - Dr. Hollis Potter

Tempus brings genomics and AI into practical care pathways that matter for Palm Coast and broader Florida oncology: by combining comprehensive DNA/RNA sequencing, algorithmic tests, EHR integration, and real‑time clinical trial matching, the platform helps community providers surface targeted therapies and enroll patients into trials without sending clinicians to a different workflow - features available through Tempus' precision‑medicine platform and clinician tools like Tempus One and Tempus Hub (Tempus AI-enabled precision medicine platform).

Tempus Next's care‑pathway intelligence layers multimodal data (imaging, labs, notes) into the point of care to reduce missed biomarker tests and close follow‑up gaps - exactly the kind of intervention that can turn an outpatient visit in Palm Coast into a concrete next step rather than a referral limbo (Tempus Oncology care pathway solutions).

The practical payoff is measurable: more trial matches, richer molecular profiles for treatment selection, and a pathway to equitable access so patients in community settings benefit from the same data‑driven options as academic centers.

Metric	Value
Oncologists using Tempus	6.5K+
Patients identified for trials	30K+
De‑identified research records	8M+
Operational countries	40+

“We envision a world where the full range of molecular profiling is available as part of the standard of care - not just in cancer, but in cardiology, neurology, immunology, and every other category of disease.” - Terron Bruner, Chief Commercial Officer, Tempus

NVIDIA's BioNeMo framework is rewriting the rulebook for in‑silico drug discovery in ways local Florida labs and biotech teams can realistically tap: foundation models like AlphaFold2, DiffDock and MolMIM - packaged as easy NIM microservices - let researchers predict protein structures, dock ligands, and generate candidate molecules at GPU‑scale, turning months of wet‑lab guesswork into rapid virtual experiments (see the BioNeMo on GKE blueprint for deployment patterns and NIMs BioNeMo on GKE deployment blueprint and NIMs).

Industry users report dramatic speedups - Deloitte cut model‑training runs from four weeks to eight hours using DGX Cloud and BioNeMo, while Astellas achieved 50–60x faster conformational screening and antibody modeling - which translates for community research centers into fewer lab cycles, cheaper screens, and faster go/no‑go decisions for promising targets (Deloitte BioNeMo customer story on generative AI in drug discovery).

For Palm Coast and wider Florida partners, that means the same cloud‑backed toolchain used by global teams can accelerate local translational projects, virtual screening campaigns, and prototype therapeutics without buying a supercomputer overnight.

“A paradigm shift in drug discovery research is about to occur as a result of the convergence of high-performance computing environments and generative AI. Through NVIDIA BioNeMo and Tokyo-1, we will continue to shorten the overall drug discovery pipeline and ultimately bring innovative new drugs to patients as quickly as possible.” - Mori

Ada's AI-powered symptom checker and health-management app can be a practical “first stop” for Palm Coast residents who want fast, evidence‑based guidance before a clinic visit: the app combines a five‑minute guided interview, symptom tracking, and exportable reports so patients can take a concise summary to their clinician, and peer‑reviewed evaluations plus Ada's own research page document high accuracy and safe triage performance across many settings (Ada symptom checker and health-management app; Ada research and peer-reviewed publications).

Backed by large‑scale usage - millions of users and tens of millions of completed assessments - and clinical studies showing strong condition‑suggestion and urgency‑advice metrics, Ada can help Florida practices reduce low‑acuity ED visits and speed the front‑door conversation by turning scattered symptom notes into structured, shareable information; a vivid payoff is that Ada's knowledge base has supported millions of assessments, creating a public health signal that clinics can use to spot local trends early (clinical vignette evaluations of symptom checkers).

Metric	Value
Users	14 million
Symptom assessments completed	35 million
App store ratings	≈4.7 (iOS / Android)

Wearables and telerehab are turning stroke recovery and outpatient rehab in Florida from guesswork into measured progress: lightweight suit‑style sensors can capture gait before and after therapy so clinicians finally see the asymmetry between feet that matters for function, as shown in a recent case report on suit-type wearable gait analysis (case report on suit-type wearable gait analysis - PubMed: suit-type wearable gait analysis case report (PubMed)); randomized trials of wearable powered robots have demonstrated real gains in gait speed for rehabilitation patients (randomized trial of wearable powered robots improving gait speed - J NeuroEngineering & Rehabilitation: wearable powered robot randomized controlled trial (J NeuroEngineering & Rehabilitation)), and pilot work on remote intelligent rehab platforms proves that guided, sensor-driven exercises can be delivered and monitored at a distance (pilot study of a wearable remote rehabilitation training system - JMIR mHealth: wearable remote rehabilitation training system pilot (JMIR mHealth)).

For Palm Coast clinics, the practical win is clear: objective, home-friendly monitoring that converts vague progress notes into quantifiable gait metrics clinicians can act on, reducing unnecessary trips and focusing in-person visits where they matter most.

Study	Key takeaway
Suit-type wearable gait analysis (2025 case report)	Captures pre/post gait metrics to guide rehabilitation
Wearable powered robot RCT (2023)	Potential to improve gait speed in stroke rehab
JMIR remote rehab pilot (2023)	Demonstrates feasibility of remote, sensor-driven training
Systematic review (2021)	Accelerometers and activity monitors are common and useful for post-stroke mobility assessment

FundamentalVR's Fundamental Surgery platform brings a “flight‑simulator for surgery” feel to Palm Coast training programs, combining HapticVR touch feedback, multi‑user holographic collaboration and cloud analytics so surgeons and OR teams can rehearse procedures, track competency and upskill without risking patients; the platform's mix of immersive VR, measurable debrief dashboards and off‑the‑shelf hardware makes it a practical fit for community hospitals and training centers looking to scale simulation affordably (Fundamental Surgery platform).

That realism matters for rare or high‑stakes cases - AAO's VR education program, built with FundamentalVR, targets neonatal ROP training where hands‑on opportunities are limited and simulation can accelerate competency across wide geographies (AAO VR Education program).

Recent platform updates add AI‑driven tutoring and predictive performance signals that analyze telemetry in real time (vendor reports cite high predictive accuracy), giving supervisors clear, objective measures to shorten learning curves and redeploy scarce instructor time where it matters most.

Metric	Value
Founded	2012
Competency sessions conducted	>15,000
Learning modalities	HapticVR, HomeVR, CollaborationVR

“Our AI Tutor empowers learners by providing intuitive mentoring, driven by an expert knowledge base, providing navigation and interaction cues within the simulation. By focusing on learner autonomy and personalized, adaptive learning support, we are able to cultivate user engagement while fostering a culture of continuous improvement.” - Vicky Smalley, CTO, FundamentalVR

Closing the loop on Palm Coast's Top 10 means moving from impressive pilots to disciplined, trust‑building deployment: adopt a clear governance framework, run regular bias and safety audits, and embed clinician‑and‑patient voices so models are validated against local Florida populations rather than distant datasets.

Expert guidance stresses exactly this mix - Northeastern responsible AI best practices for healthcare (Northeastern responsible AI best practices for healthcare) while a recent PMC review on AI governance and risk mitigation underscores governance as critical to scaling enterprise AI safely (PMC review on AI governance and risk mitigation).

Practical steps for Palm Coast systems include an AI operations committee, routine model audits to surface biases (a pressing concern for communities where 64% of Black adults report racial bias as a medical issue), strict HIPAA‑aligned data protections, and measurable staff upskilling - training that nontechnical clinicians can begin through programs like Nucamp's 15‑week AI Essentials for Work bootcamp registration (Nucamp AI Essentials for Work bootcamp registration).

Responsible adoption isn't a brake on innovation; it's the infrastructure that turns AI pilots into equitable, sustainable care improvements for patients and teams across Florida.

Governance element	Why it matters
Clear governance framework	Defines roles, oversight, and accountability
Regular audits	Detects bias and safety issues before deployment
Stakeholder engagement	Ensures local validity and trust
Training & education	Builds clinician competency and oversight
Data privacy & validation	Protects PHI and ensures local performance

“We believe our Responsible AI approach can help raise the bar for the industry and drive the adoption of ethics and risk management best practices.” - Pfizer