Deploying computer vision and AI models to assist clinicians. For example, our systems can analyze radiology or pathology images to highlight tumors or anomalies that might be missed by the human eye. We integrate AI tools into workflows so that a doctor’s review of a scan includes AI-generated annotations as a “second opinion.” We also build predictive models that analyze vital signs and lab results to forecast patient deterioration (like sepsis risk) hours in advance, enabling preemptive care. All models are validated with medical experts and designed to be interpretable to earn clinical trust.

Using AI and bioinformatics on genomic and patient data to tailor treatments. We develop pipelines that process DNA sequencing and correlate genetic markers with patient outcomes. This enables precision therapies (for example, choosing a cancer drug most likely to work based on a tumor’s genetic profile). We also create decision-support tools that consider a patient’s genetics, history, and lifestyle to recommend treatment plans or medication dosages.

Reducing administrative burdens in clinics and hospitals. We introduce RPA and AI to handle tasks like appointment scheduling and reminders, insurance eligibility checks, billing, and claims processing. For example, bots can verify insurance information or process admission paperwork automatically. We also use analytics to optimize patient flow: predicting ER surges, optimizing staff schedules, and managing bed assignments. This minimizes wait times and lets healthcare staff focus more on patient care.

Enhancing virtual care. We set up secure telehealth platforms with integrated video, scheduling, and medical device data. We deploy AI-driven triage chatbots or symptom checkers that guide patients to the right care level (self-care, teleconsult, emergency). We implement remote patient monitoring by connecting IoT devices (like glucose monitors or heart monitors) to analytics dashboards. AI algorithms flag concerning trends (e.g., weight gain in a heart patient), alerting clinicians before conditions worsen. These solutions are integrated with EHRs and adhere to telehealth security standards to protect patient privacy.