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Artificial Intelligence and Machine Learning might have been considered the future of healthcare not that long ago, but things have changed. What was once considered futuristic is the real world we inhabit now, and the rate the industry is being transformed by these powerful drivers is astonishing to witness. Let’s explore some of the areas being revolutionized before our eyes.
Mаchine Learning is very effective in diagnostics and recognizing different types of diseases that are typically very difficult to detect, especially in the initial stages, when early diagnostics could be life-saving. Such technology can be deployed in various healthcare sectors to detect different types of cancer, neurological conditions, pathogens, etc.
Machine Learning models can be widely deployed and very effective. They could be based on physiological, environmental, and genetic data that helps discover risk factors and improve the diagnostic accuracy. This results in better treatment efficiency and reduction of unnecessary hospital visits whenever remote examination is possible.
The COVID-19 pandemic has proved that Artificial Intelligence could be key to limiting the infection spread. ML facilitates the processing of satellite information, social media trends, and news websites to make conclusions on epidemic outbreaks around the globe to gain better control of them.
Unlike random testing, ML comprehensive testing strategies allow researchers to predict the possible scope of the epidemic at its very start. They can also reduce the infection spread when specific age groups or geographic areas are recognized to be potentially at risk, and necessary measures are taken as a precaution.
Machine Learning algorithms can model drug components that treat similar diseases, using existing records of their effect on patients. This would facilitate personal medication for individuals with certain combinations of illnesses and unique requirements. Machine Learning helps researchers leverage past and present research to make the preclinical process more efficient and Deep Learning facilitates finding new patterns in relatively unexplored data sets.
Clinical research and trials of new medications are an arduous and costly process. However, sometimes the time to market for a specific drug or vaccine needs to be accelerated to the maximum. You really do not need to look further than the COVID-19 vaccines and the unprecedented speed they became available. Luckily, ML algorithms reduce data-based errors by detecting the best samples and analysing the ongoing data from the trial participants.
Accurate diagnostics is critical for effective treatment. That is why treatment recommendation AI can play a significant role in improving healthcare quality. Reinforcement Learning (RL) is Machine Learning that makes decisions based on analysing experience.
This means Reinforcement Learning practically emulates the decision-making process of knowledgeable physicians. While not fully deployed in replacing actual doctors, Reinforcement Learning has been used for clinical trial dosing in simulation settings and determining the medication dosage.
Robots are not here to take our jobs away. But they can replace or augment human operators and do 24/7 routine work that does not require emotional intelligence, creativity, or critical thinking. Healthcare organizations typically utilize them to free up resources, improve customer satisfaction, reduce costs and deliver better business value.
Chatbots and automated surveys facilitate patients to resolve issues without the help of a physician. They collect and use patient interaction data to improve service quality and provide reminders and motivational messages. This way, the automation of repetitive tasks lets healthcare specialists concentrate on emergencies or more complicated cases.
Chatbots are evolving and getting easily accessible and inexpensive, so the industry is expected to be taking even more advantage of them. The Scalefocus remote software development centers have extensive experience building chatbot solutions that are tailor-made to our partners’ business models.
Smartwatches, bio patches, smart hearing aids, smart pills – these wearables are also known as the Internet of Medical Things (IoMT) and make healthcare more connected than ever. They finetune treatment programs by using precise statistics on the patients’ sleep and nutrition habits or average activity level and sending real-time information on their health state to their doctors.
Patients increasingly prefer contacting physicians remotely and getting actual treatment only if necessary. That means at least two things – self-care is a trend that is here to stay, and the wearables’ role is only getting more significant. They detect tendencies or anomalies in the patients’ regime and suggest possible modifications for a healthier lifestyle and disease prevention.
Scalefocus has gained solid experience working with healthcare organizations, including anindustry leader that utilizes our offshore development centers as service providers. Such expertise has allowed us to develop end-to-end platforms and wearables like the award-winning SoFit device – a scalable integrated system for patients who need remote Physical Therapy or Kinesiotherapy. It provides on-demand Telehealth services, allowing for complete rehabilitation treatment even without a physician’s presence.
Read on to find out more about another one of our finest healthcare solutions.
SAAM stands for Supporting Active Ageing Through Multimodal Coaching and is basically a virtual assistant platform. It tackles the feeling of isolation and depression among ageing people by boosting their well-being and supporting a more active and connected lifestyle. The platform uses unobtrusive personal and smart home sensors to enhance human interaction and help the elderly stay mobile and socialised.
The platform utilizes Machine Learning, user profiling and interfaces, affective computing, and modal coaching.
As a result, SAAM enables caregivers to:
- Coach the social circle of elderly people and get in touch and support them when needed;
- Suggest social and cultural events based on the preferences and interests of the users;
- Support the seniors’ group activities;
- Embrace a platform for telemedicine, telework, and integrated social services.
What SAAM does to assist older persons in their everyday tasks and well-being at home:
- Collects health, emotional and cognitive data from sensors, smart meters, video, and audio receivers;
- Monitors vital functions and medication take-in;
- Detects mood and behavior changes;
- Provides recommendations for healthy diets and hobbies;
- Detects injuries and prevent risk situations (falls, burning, illness) by monitoring their domestic environment.
- SAAM is a Scalefocus proprietary project and its concept is derives from our vast Machine learning and healthcare experience. Through the years we have turned into an innovation partner to numerous industry disruptors and have helped them utilize the latest technologies to improve customer experience and digitalization.
Medical Diagnostics, Epidemic Control, Drug Discovery, and Clinical Research are among the areas Machine Learning and Artificial Intelligence are putting their stamp on while driving modern healthcare forward. The Internet of Medical Things has made self-medication more accessible and reliable than ever, and Chatbots now provide 24/7 support while healthcare organizations free up resources.
Choosing Scalefocus for a trusted technology and IT outsourcing partner has helped our partners leverage cutting-edge technology and a world-class team of software engineers, data scientists, and project managers to stay at the forefront of innovation.
We are passionate about all things healthcare, so why not contact us and have a chat about your projects and how we can assist?