IA EN LA DETECCIÓN Y EL DIAGNÓSTICO DE ENFERMEDADES
A diferencia de los humanos, la IA nunca necesita dormir. Los modelos de aprendizaje automático podrían usarse para observar los signos vitales de los pacientes que reciben cuidados intensivos y alertar a los médicos si aumentan ciertos factores de riesgo. Si bien los dispositivos médicos como los monitores cardíacos pueden rastrear los signos vitales, la IA puede recopilar los datos de esos dispositivos y buscar afecciones más complejas, como la sepsis. Un cliente de IBM ha desarrollado un modelo de IA predictivo para bebés prematuros que tiene una precisión del 75% en la detección de sepsis grave.
Tratamiento personalizado de enfermedades
La medicina de precisión podría ser más fácil de respaldar con la ayuda de la IA virtual. Debido a que los modelos de IA pueden aprender y retener preferencias, la IA tiene el potencial de proporcionar recomendaciones personalizadas en tiempo real a los pacientes las 24 horas del día. En lugar de tener que repetir la información a una nueva persona cada vez, un sistema de atención médica podría ofrecer a los pacientes acceso las 24 horas a un asistente virtual impulsado por IA que podría responder preguntas basadas en el historial médico, las preferencias personales y las necesidades del paciente.
IA en imágenes médicas
La IA ya está desempeñando un papel destacado en el área de las imágenes médicas. Las investigaciones han indicado que la IA impulsada por redes neuronales artificiales puede ser tan eficaz como los radiólogos humanos para detectar signos de cáncer de mama y otras afecciones. Además de ayudar a los médicos a detectar signos tempranos de la enfermedad, la IA también puede ayudar a que la asombrosa cantidad de imágenes médicas que los médicos deben monitorear sea más manejable al detectar partes vitales del historial de un paciente y presentarles las imágenes relevantes. .
Eficiencia de los ensayos clínicos
Durante los ensayos clínicos, se dedica mucho tiempo a asignar códigos médicos a los resultados del paciente y actualizar los conjuntos de datos relevantes. La IA puede ayudar a acelerar este proceso al proporcionar una búsqueda más rápida e inteligente de códigos médicos. Dos clientes de IBM Watson Health descubrieron recientemente
GuardadoWHAT IS ARTIFICIAL INTELLIGENCE IN MEDICINE?
Machine learning can help process medical data and provide medical professionals with important information, improving health outcomes and patient experiences.
Artificial intelligence in medicine is the use of machine learning models to search medical data and discover insights that help improve health outcomes and patient experiences..
Currently, the most common functions of AI in medical environments are clinical decision support and image analysis. Clinical decision support tools help providers make decisions about treatment, medications, mental health, and other patient needs by giving them quick access to information or research that is relevant to their patient. In medical imaging, artificial intelligence tools are being used to analyze CT scans, X-rays, MRIs and other images for lesions or other findings that a human radiologist might miss.
The challenges that the COVID-19 pandemic created for many health systems also led many health organizations around the world to begin field testing new AI-enabled technologies, such as algorithms designed to help monitor patients and tools powered by AI to evaluate COVID-19 patients.
The research and results of these tests are still being compiled, and general standards for the use of AI in medicine are still being defined. However, the opportunities for AI to benefit physicians, researchers, and the patients they serve are constantly increasing. At this point, there is little doubt that AI will become a central part of the digital health systems that shape and support modern medicine.
Applications of AI in medicine
There are numerous ways AI can positively impact the practice of medicine, whether by accelerating the pace of research or helping doctors make better decisions. Here are some examples of how AI could be used:
AI in disease detection and diagnosis
Unlike humans, AI never needs to sleep. Machine learning models could be used to observe the vital signs of patients receiving intensive care and alert doctors if certain risk factors increase. While medical devices like heart monitors can track vital signs, AI can collect the data from those devices and look for more complex conditions, like sepsis. An IBM customer has developed a predictive AI model for premature babies that is 75% accurate in detecting severe sepsis.
Personalized disease treatment
Precision medicine could be easier to support with the assistance of virtual AI. Because AI models can learn and retain preferences, AI has the potential to provide real-time personalized recommendations to patients 24 hours a day. Instead of having to repeat information to a new person each time, a healthcare system could offer patients 24-hour access to an AI-powered virtual assistant who could answer questions based on medical history, the patient’s personal preferences and needs.
AI in medical images
AI is already playing a prominent role in the area of medical imaging. Research has indicated that AI powered by artificial neural networks can be as effective as human radiologists at detecting signs of breast cancer and other conditions. In addition to helping doctors detect early signs of disease, AI can also help make the staggering amount of medical images doctors must monitor more manageable by detecting vital parts of a patient’s history and presenting them with the relevant images. .
Efficiency of clinical trials
During clinical trials, a lot of time is spent assigning medical codes to patient outcomes and updating relevant data sets. AI can help speed up this process by providing faster and smarter searching for medical codes. Two IBM Watson Health customers recently discovered