Operations
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Collaborate on documents, organize tasks, and access your Notion content without switching between applications.
Automate note-taking for doctors, save time, cut down on mistakes, and guarantee precise records.
Research
Summarize and understand key insights in medical research, saving time and enhancing patient care.
Speed up hospital discharge note writing, reduce doctors' workload, and minimize patient risks.
Patient Care
Create tailored clinical plans for patients combining patient cases with medical literature to enhance care and reduce provider workload.
Clinical Research
Ask questions and get the latest medical research with this AI research assitant, improve patient care and stay up-to-day.
Early Detection
Detect CKD risk from clinical variables and prioritize patients for enhaced care and cost reduction.
Identify high-risk HF patients, guide them into care programs, and reduce hospitalizations and costs.
Predict high-risk diabetes patients for early intervention, reducing complications and costs.
Use AI to identify COPD in patients using key EMR symptoms.
Access
Detect patients that will have increase rates of mortality and negative obstetric outcomes using clinical variables
Use patient intake data to predict the length of stay at hospitalization.
Use clinical variables from the EMR of patients to predict antibiotic resistance
Poor medication adherence causes 125k deaths, 10% hospital admissions, costs $300B yearly. AI can boost adherence, reduce risks.
Supply Chain
Predict stock levels to optimize inventory management, anticipate demand for finished products and reduce costs.
Approximately 30–40% of all delirium episodes are considered to be preventable, AI identifies high risk patients.
Urinary tract infections (UTIs) impose significant health and financial burdens, AI allows providers to intervene accordingly
AI can help healthcare organizations (HCOs) identify individuals at-risk for developing Metabolic syndrome (MetS).
AI-based models can accurately predict which patients are most likely to experience adverse events.
Predictive analytics enable practitioners to proactively identify high-risk patients and prevent serious fall-related injuries.
Readmissions are expensive for hospitals. AI identifies who are the most likely to be readmitted to take preventive measures.
Operational efficiency determines profitability for healthcare organizations (HCOs), AI boosts productivity up to 44%.
Improving the product mix increases competitiveness, customer satisfaction, profitability and efficiency
AI systems can use past trends and market signals to forecast demand.
Access to the market in the pharmaceutical industry refers to identifying, evaluating, and taking advantage of market opportunities effectively.
Artificial Intelligence is crucial in enhancing price accuracy in medical device companies, consumer healthcare enterprises, and pharmaceutical firms.
33% of clinical trials have problems with randomization, statistical analysis and patient recruitment. AI assists in several bottlenecks.
Frailty can be managed and reduced between 35 and 45%.
Nearly 20% of patients are hospitalized again within 30 days, preventing these events is a priority for healthcare organizations
More than one in three patients that prefer palliative care do not receive it. AI ensures patients the quality of life they desire in their final days
Predict the likelihood of various health outcomes by identifying early factors.
Prevent patients from consuming an overprescribed amount of opioids and predict which patients are likely to suffer from opioid abuse
Hospitals can leverage predictive analytics to identify patients likely to be at high risk for undesirable complications.
A way to identify patients at risk for ER visits and observation stays, surface modifiable risk factors, and streamline patient outreach.
Readmitted patients are often clinically unstable at the time of transfer, AI ensures the transition to skilled nursing facilities goes smoothly.
Increase appointment attendance rates, reduce the financial burden of no-shows, and improve the health outcomes with Artificial Intelligence
Churn reduces medication adherence and disrupt continuity of care, and patients with coverage interruptions have more emergency department use.
Prior Authorization (PA) delays access to necessary care, Healthcare organizations an leverage AI to streamline PA.
Medical
Telehealth is cost-effective and frequently able to address patient health needs without escalation to more resource-intensive services.
Predict drug adverse effects with Artificial Intelligence, increasing patient health and satisfaction.
Proactively identifying such rising risk patients is important to mitigate future health related costs.
Improve omnichannel engagement with data-driven, personalized approaches
Deep personalization of Patient Support Programs with digital technologies to enhance patient experience and adherence.
Adherence to medical guidelines is a global issue, specially on chronic patients. AI helps medical professionals and patients to follow guidelines.
Automated Inventory Management, order routing, demand forecasting and Supply Chain Optimization with AI
About 1 in 8 women will develop invasive breast cancer throughout their lifetime. Prevent it by identifying potential signs at an early stage.
Cervical cancer prediction with Artificial Intelligence to improve the accuracy and efficiency of early detection and diagnosis of cervical cancer.
Predicting and preventing suicide, particularly through the use of machine learning algorithms
Addressing challenges in triage services with AI by automating tasks and reducing waiting times in waiting lists and administrative burden.
Diagnosing rare diseases is difficult and time-consuming, and there is often no cure. AI improves diagnosis and treatment for patients.
Advanced AI to Detect Drugs and Adverse Reactions in Text from Social Media
AI offers educational support tools for doctors in their daily basics to efficiently manage patients.
An Expert AI Assistant for Writting Insurance Approval Letters
30% of patients with diabetes develop disease-related complications. AI-based assistants offer personalized recommendations to improve habits.
Lung cancer screening based on various critical lung cancer risk factors, including age, smoking history, and family cancer history
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