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Automate note-taking for doctors, save time and cut down mistakes.
Summarize patient data and get concise information based on medical history
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.
Create tailored clinical plans for patients combining patient cases with medical literature to enhance care and reduce provider workload.
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.
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.
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).
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.
33% of clinical trials have problems with randomization, statistical analysis and patient recruitment. AI assists in several bottlenecks.
Hospitals can leverage predictive analytics to identify patients likely to be at high risk for undesirable complications.
Increase appointment attendance rates, reduce the financial burden of no-shows, and improve the health outcomes with Artificial Intelligence.
Prior Authorization (PA) delays access to necessary care, Healthcare organizations an leverage AI to streamline PA.
Predict drug adverse effects with Artificial Intelligence, increasing patient health and satisfaction.
Deep personalization of Patient Support Programs with digital technologies to enhance patient experience and adherence.
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.
Early detection and personalized treatment of prostate cancer.
Gastric cancer prediction with Artificial Intelligence to improve accuracy and efficiency in early detection and diagnosis of gastric cancer.
Prediction of hematologic cancers through AI to enhance the precision and efficiency in early detection and management of blood cancers.
CVDs cause millions of deaths and high costs; AI can identify high-risk patients, improve care, and reduce expenses.
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