It is no secret that artificial intelligence is expected to have a ground breaking impact in the healthcare sector. From chronic diseases and cancer to radiology and risk assessment, there are endless opportunities to leverage machine learning algorithms to deploy more precise, efficient, and impactful interventions at exactly the right moment for a patient.
Next, we list our solutions for Healthcare enterprises.
Intelligent medical imaging can analyze and identify diseases images to support the health
decision-making process. Examples of this solutions can be using images to characterize the
phenotypes and genetic properties of tumors; or collecting images to classify skin lesions,
wounds or infections.
Automated agents can suggest the best treatment based on the patient historical data and put in
mechanisms to detect and prevent possible diagnosis errors. Bots can be specially useful in
cases where the illness is low risk allowing the health professionals to focus on more
important or urgent cases.
Whether you are a doctor, a nurse or a recovering patient, Internet of Things (IoT) solutions
provide endless opportunities for real-time health monitoring. Smart wearables can transmit
securely and effectively patient status, data and other pertinent health information to the
staff in emergency situations.
Late diagnosis of treatable illnesses is one of the biggest causes of avoidable deaths. The use of Big Data and AI for early detection and diagnosis could fundamentally transform outcomes for people with different chronic diseases, such as heart diseases, prostate cancer or lung cancer, as well as saving hospitals money.
There is a high variability in patient drug response due to genetic factors, age,
nutrition habits, health status and environment conditions. Machine learning can be
used to analyze vast amounts of data and provide insights to help the doctor provide
optimal diagnostics and treatments.
Having a medical device fail in an operating room can lead to complications due to prolonged
anaesthesia, risk of infection or wasted time in inconvenient replacement of the device.
Monitoring the life-cycle and being able to anticipate impeding failures
of the device provide a competitive advantage to medical instrumentation manufacturers.
AI can address this problem by monitoring internet connected devices
and performing predictive maintenance of those that are in sub-optimal
state to schedule maintenance requests and prevent
undesirable device down time.