Artificial intelligence has promising applications in healthcare. AI helps analyze radiographs, predict the needs of the hospital and medical departments, develop medication faster. It helps pathologists and histologists diagnose patient samples, assists physicians in surgeries, in setting drug doses, or reducing dosage errors in chronic diseases.
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| Importance of Artificial Intelligence in Modern Healthcare System |
Why is Artificial Intelligence Important in Healthcare?
Today! The medical world
is living with an enormous amount of DATA, which has arisen from laboratory
tests and clinical and physiological observations.
As clinicians began to
shift in clinical practice from accidental analysis and reliance on the
accuracy of their observation to the analysis of different data and structured
algorithms, based on continuously updated sets of data to improve the ability
to diagnose a disease or predict patient outcomes.
Several types of AI are
already in use by the world's health care providers and drug and food
development companies.
With algorithms already
surpassing radiologists in detecting malignant tumors and guiding researchers
in how to build clinical scientific trials with the help of artificial
intelligence, it will take several years before official bodies and
international health organizations adopt the use of artificial intelligence as
a reliable medical partner.
AI technology can be tried
in matters such as analyzing data, and this requires the machine to learn something
called Natural Language Processing.
There are many medical
procedures that appear on demand for a patient designate properly taken to
attention, such as:
- Collecting information data from patient discussions and checks.
- Applying several causes of information data to derive an exact identification.
- Defining an applicable cure technique.
- Arranging and controlling the selected cure technique
- Treating and examining outcomes of the result.
- Rehabilitation, continuation arrangements.
- Observing patient involvement in decision making.
Although there are many
cases in which artificial intelligence can perform the required work better or
similar to humans, the ethical issue in enabling the machine to bear the
responsibility for health care maintains the human control of this machine and
therefore the machine remains the assistant and not the medical
decision-maker.
Therefore, machine
learning cannot replace the doctor, but doctors who learn and use Artificial
Intelligence will replace the traditional doctors who do not keep up with the
new digital revolution.
Role of Artificial
Intelligence in Healthcare and Medicine
The field of healthcare is
evolving at an increasing speed, and this is accompanied by a significant
increase in the amount of data and challenges in terms of cost and patient
outcomes, so AI applications have been used to reduce these challenges.
Artificial Intelligence is
very useful in solving problematic healthcare challenges and offers a number of
advantages over traditional data analytics and clinical decision-making
techniques.
The following are the most
important examples of the role of artificial intelligence (AI) in healthcare
and medicine:
AI in
Medical Diagnosis: Artificial Intelligence has the potential to revolutionize
medical diagnostics.
Unnecessary routine
laboratory testing increases unnecessary financial costs. Therefore, artificial
intelligence applications have been used to narrow the circle of laboratory
analyzes that the patient may need.
AI can detect the presence of early disease as soon as possible as it can automate a large portion of the manual work and speed up the diagnosis process.
Improving Clinical
Workflow: Artificial intelligence is currently being used to efficiently manage
workflow and analyze imaging.
AI can be used to improve
clinical workflow, support better clinical insights, reduce clinical
variability, aid in setting study priorities, and minimize physician burnout.
Artificial intelligence
has the power to take over the time-consuming task of data input so that
clinicians can focus on improving labor utilization, increasing daily
productivity and providing the highest quality of care to patients.
Predicting ICU Transfers: Unplanned transfer of patients to the ICU can have poor outcomes and sometimes even death in patients.
Therefore, artificial intelligence has been used to reduce the percentage of these cases, by finding patients with severe cases.
As artificial intelligence systems use patients 'medical records, laboratory results, and their vital signs to manage patients' condition before it deteriorates, and forcing them to be transferred to the intensive care unit.
Artificial intelligence systems can guide clinicians on where to start treatment.
Predicting Hospital
Acquired Infections: Artificial intelligence can standardize the diagnosis of
infections with Infection Prevention and Control (IPC) implications, and
facilitate the dissemination of IPC expertise. AI provides opportunities to
improve diagnosis through objective pattern recognition.
Using AI-driven models,
clinicians can monitor high-risk patients, predict which patients are most
likely to develop central-line infections and intervene to reduce risk.
Developing the Next
Generation of Radiology Tools: Artificial intelligence can help develop
the next generation of imaging tools that will provide accurate information and
detailed enough to replace the need for tissue samples in some cases.
The next generation of
artificial intelligence is expected to be more effective in the healthcare
system and there will be further improvements in performance.
All of these developments promise to increase accuracy and reduce the number of routine tasks that exhaust time and effort.