Technological innovation in healthcare can be often very risky. Medical professionals and patients alike base their trust on research, proven clinical trials, and repetitive results. And tech itself, which leads to an unparalleled quality of life for patients. The same goes for artificial intelligence. AI provides valuable insights, improves decision-making, enhances patient outcomes, and streamlines processes. From early disease detection to personalized treatment plans, it helps people make the most of today’s medicine. What are the best AI tools in healthcare? What can we learn from them?
Best AI medical software of 2024
The situation with COVID-19 accelerated many projects and AI-related software applications. Here’s a list of some of the most interesting AI tools for medical professionals.
- Enlitic. This is a leading, AI-based medical image analysis software. The tool compares radiology reports against corresponding images, preventing false alarms, and spotting diseases early on. It enhances workflow, and efficiency, and provides better insights.
It also helps medical professionals by presenting patient data, which leads to improved billing processes.
- Buoy Health. It’s a solution that offers a personalized symptom checker powered by artificial intelligence and advanced machine learning. It combines user-reported symptoms with the latest medical knowledge to provide personalized insights into patients’ individual situation.
Through the marketplace, the solution provides treatments for physical, mental, and specialized health needs.
- Regard (previously Health Tensor). The solution uses artificial intelligence and machine learning to automate diagnosis, create accurate notes for doctors, and remove administrative tasks. The product works with electronic health records (EHRs) to examine patient information, suggest diagnoses, and automate note-writing.
Regard is an interesting product for clinicians and administrators alike, simplifying everyday tasks and introducing AI as a companion and powerful tool.
- PathAI. Who’s saying that healthcare is limited only to living? Pathology also benefits from technological advancements. Path AI specializes in applying artificial intelligence and machine learning to pathology. Product’s goal is to improve accuracy and efficiency in diagnosing diseases through advanced image analysis and data-driven insights.
Key aspects of this product include digital pathology, disease diagnosis and classification, prognostic and predictive analytics, and drug development and research.
- Butterfly Network. The company specializes in developing handheld, pocket-sized ultrasound devices powered by artificial intelligence. Their innovative technology combines hardware and software to provide accessible and high-quality medical imaging solutions.
Key applications of the product include point-of-care imaging, AI image enhancement, deep learning guidance, cloud-based storage and collaboration. Combining advanced imaging capabilities with usefulness in resource-limited or remote settings makes Butterfly Network a powerful, AI-driven solution.
- Suki. The company’s messaging asks a simple question: “Want to spend more time with patients and less time with the computer?” Suki is a solution. The product is an AI-powered, voice-enabled digital assistant that alleviates the pressure of documentation from doctors, allowing them to focus more on their patients. This intelligent assistant streamlines administrative tasks and accesses necessary patient data from the EMR with speed and accuracy.
Suki offers a voice-enabled digital assistant, handling of administrative tasks, natural language processing, easy integration with popular EMRs, and reduction in medical documentation time.
- Linus Health. The company offers early detection of cognitive and brain disorders, provides actionable clinical insights for healthcare providers, and delivers personalized action plans for individuals. It’s cognitive assessment feature merges trusted cognitive tests with AI-enhanced brain analysis for efficient and scientifically validated early detection of cognitive impairment.
The company has proven technology. It’s AI-upgraded version is backed by 10 years of research from top medical institutions and has proven effective in over 20 studies.
- Cumulus Neuroscience. It’s an AI and cloud-based brain physiology analysis tool for clinical trials. The company utilizes datasets to provide new insights in five key measurement domains (cognition, EEG, mood, language, and sleep), and is validated to show the effects of age, disease, and therapy.
The platform captures objective longitudinal data across a broad spectrum of modalities, including EEG. This delivers insights to transform clinical trials in the area of brain disorders.
- Eleven. It’s an AI-based RNA drug development platform for researchers. The company harnesses the power of combinatorial chemistry and AI to transform RNAi drug development into a programmable process against influenza and SARS-CoV-2.
The company is backed, among others, by Campbridge University and Bill & Melinda Gates Foundation.
- BIOS. The company is a provider of AI-based platforms to diagnose nervous system disorders. It uses machine learning technology to help identify the defects in the neural signals, which is causing various chronic illnesses. Hypertension, blood pressure, and more can be treated and help practitioners optimize the reasons for the neurological disorders. Also, plan the diagnosis for better treatment outcomes.
BIOS has developed a programming language for the nervous system that can be used for discovering insights into human diseases, thus leading to new treatments. Real-time insights and precision targeting provide software-delivered therapies.
What is the impact of AI in healthcare?
AI transforms healthcare through automation, data analysis, decision support, and more. With artificial intelligence, professionals can enhance images to detect abnormalities, quicker optimize treatments based on patient data and current state, use virtual assistants (digital nurseries) and accelerate drug discovery through the prediction of effective compounds.
The end result is safer and more personalized medicine. Which is the future of medicine itself. AI accelerates this transition.
What can we learn from it?
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