How Is Artificial Intelligence Transforming the Medical Diagnosis?
Artificial intelligence (AI) transforms according to the interaction, consumer information, and goods and services across industries. In the healthcare industry, AI is already changing patients’ experiences, how clinicians practice medicine, and how the pharmaceutical industry operates.
Although, Artificial Intelligence plays an important role
in different aspects of medical diagnosis like medical decision making,
management, automation, admin, and workflows. It can be used to diagnose
cancer, triage critical findings in medical imaging, acute flag abnormalities,
help radiologists prioritize life-threatening cases, diagnose cardiac
arrhythmias, predict stroke outcomes, and help manage chronic diseases.
Since the, 1970s diagnostics and treatment have been the
prime focus of AI, as MYCIN was developed at Stanford for diagnosing
blood-borne bacterial infections. MYCIN and other early rule-based systems
showed promise for diagnosing and treating disease accurately but were not
adopted for clinical practice. They were not substantially better than human
diagnosticians, and they were poorly integrated with clinical workflows and
medical record systems.
AI is a rich realm of data, algorithms, analytics, deep
learning, neural networks, and insights that is growing and adapting to the
needs of the healthcare industry and its patients. Although, over the past few
years, artificial intelligence in medical care has reduced the extreme pressures
felt by the medical industry and is constantly working to evolve in
diagnostics. Recently IBM’s Watson received considerable attention in the media
for its focus on precision medicine, particularly cancer diagnosis and
treatment. As Watson employs a combination of machine learning and NLP
capabilities. However, AI seems to be still developing and soon a part of the
healthcare diagnostic industry.
To know about: -
·
Types of
AI of Relevance to Healthcare Diagnostics
·
AI
Applications in Diagnostics
·
AI Related
Developments in Diagnostics
·
Future of
AI in Diagnoses
·
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