JOURNAL OF IQRO – ЖУРНАЛ ИҚРО – IQRO JURNALI – volume 16, issue 02, 2025
ISSN: 2181-4341, IMPACT FACTOR ( RESEARCH BIB ) – 7,245, SJIF – 5,431
ILMIY METODIK JURNAL
Ergasheva Sadoqat
Tashkent medical academy
2nd year student of the Faculty of Pediatrics
Egamberdiyev Shavkatbek
Andijan state technical institute
4th year student of the direction of “Economics”
MEDICAL DIAGNOSTICS WITH THE HELP OF ARTIFICIAL INTELLIGENCE
Abstract.
This article reviews recent advances in medical diagnostics using artificial intelligence
(AI) and their practical applications. The article provides detailed information on how AI is used
in medicine, in particular in the diagnosis and treatment of diseases, its advantages and
limitations. It discusses how AI technologies, including machine learning, deep learning, and
data analysis, can improve the decision-making process of doctors. The article also provides
examples of the effectiveness of diagnostic systems based on AI and their application in clinical
practice. The ethical and legal aspects of the use of AI in medicine are also considered, and
future development prospects are discussed.
Keywords:
artificial intelligence, medical diagnostics, disease detection, treatment, SI
technologies, legal aspects.
Introduction.
Artificial intelligence (AI) is revolutionizing the medical field, particularly in the
diagnosis and treatment of diseases. These technologies can help doctors make more accurate
and effective decisions. One of the main advantages of AI is the ability to quickly analyze large
amounts of data [1]. In medicine, this includes information from various sources, such as patient
records, laboratory results, and imaging studies (e.g., X-rays, MRIs). In the diagnosis of diseases,
AI algorithms, for example, use deep learning techniques to identify specific features from
images. Such systems are used, for example, in the field of oncology to detect cancer cells.
Studies show that AI systems can sometimes perform better than human doctors [2]. This helps
to quickly assess patients' conditions and develop a treatment plan. In addition, AI allows for the
development of individualized treatment approaches in medicine. For example, by analyzing
genetic data, individual treatment strategies can be developed for a patient's diseases. This
increases the effectiveness of treatment for patients and reduces side effects. However, the
application of artificial intelligence in medicine also has a number of limitations. SI systems
require large amounts of high-quality data. If the data is incorrect or incomplete, the accuracy
and reliability of these systems can decrease. Also, the process of collecting and storing the data
necessary for the operation of artificial intelligence is often complex and time-consuming.
Artificial intelligence-based systems must use personal patient data, which raises issues of
confidentiality and data protection. These issues must be addressed in order to maintain trust
between doctors and patients. Also, artificial intelligence systems cannot fully replace the
experience of human doctors. Human factors, such as understanding the patient's condition and
emotional approach, are very important in medicine. Artificial intelligence systems are limited to
analyzing data and do not take human emotions into account.
The use of artificial intelligence in medicine is expected to expand in the future. As technology
advances, AI systems can provide more accurate and reliable results. However, ethical and legal
issues need to be considered in this process [3]. Medical professionals and researchers should be
careful when implementing AI in practice.
JOURNAL OF IQRO – ЖУРНАЛ ИҚРО – IQRO JURNALI – volume 16, issue 02, 2025
ISSN: 2181-4341, IMPACT FACTOR ( RESEARCH BIB ) – 7,245, SJIF – 5,431
ILMIY METODIK JURNAL
Artificial intelligence (AI) technologies, including machine learning, deep learning, and data
analysis, can radically improve the decision-making process of doctors in the medical field.
These technologies help doctors make more accurate and effective decisions, while also helping
them develop the best treatment strategies for patients.
Machine learning algorithms provide the ability to quickly and efficiently analyze large amounts
of data. In medicine, doctors must review a large number of patient data, laboratory results, and
imaging tests (e.g., X-rays, MRIs). Machine learning algorithms analyze this data and help
identify important features in diagnosing diseases or assessing a patient’s condition. For example,
using ML models to diagnose conditions such as heart disease or diabetes can help doctors make
faster and more accurate diagnoses. Deep learning (DL) is a powerful technique for analyzing
image data. DL algorithms are used in oncology, for example, to detect cancer cells. Studies
have shown that deep learning models can sometimes outperform human doctors [4]. This can
help doctors quickly assess patients’ conditions and develop treatment plans. Such technologies
can help doctors detect diseases in the early stages, which can improve treatment effectiveness.
Data analytics can also improve doctors’ decision-making. AI systems can collect and analyze
large amounts of patient data, and provide doctors with accurate recommendations. For example,
by analyzing a patient’s history and genetic information, AI systems can suggest individualized
treatment strategies. This increases the effectiveness of treatment for patients and reduces side
effects. AI systems also provide doctors with diagnostic tools that help them make clinical
decisions. Programs created with AI can analyze patients’ symptoms and identify their possible
diseases. This process allows doctors to expand their knowledge and apply new approaches [5].
However, the use of AI in medicine also has a number of limitations. First, AI systems require a
large amount of high-quality data. If the data is inaccurate or incomplete, the accuracy of these
systems may decrease. Ethical issues also play an important role. AI-based systems must use
patients’ personal data, which raises privacy and data protection issues. Collaboration between
doctors and AI systems is also important. AI systems cannot fully replace the expertise of human
doctors; human factors, such as understanding the patient’s condition and emotional approach,
are very important. AI systems are limited to analyzing data and do not take into account human
emotions.
Diagnostic systems based on AI have shown their effectiveness in medicine and are widely used
in clinical practice. The following are examples of the effectiveness and practical application of
these systems:
An AI system developed by Google DeepMind is used to diagnose retinopathy. The system
analyzes retinal images and helps doctors identify the early stages of the disease. Studies show
that this system can show better results than human doctors. This increases the chances of
treating patients early.
Aidoc is an artificial intelligence-based radiological diagnostic system that analyzes X-ray and
computed tomography (CT) images. The system helps detect, for example, blood clots in blood
vessels or pulmonary embolism. The Aidoc system allows doctors to make quick and accurate
diagnoses, which leads to rapid treatment of patients.
EkoAI is an artificial intelligence-based system that analyzes cardiac ultrasound scans. The
system provides accurate results in assessing the structure and function of the heart. Studies
show that EkoAI, when used by cardiologists, significantly increases the accuracy of diagnosing
heart diseases.
JOURNAL OF IQRO – ЖУРНАЛ ИҚРО – IQRO JURNALI – volume 16, issue 02, 2025
ISSN: 2181-4341, IMPACT FACTOR ( RESEARCH BIB ) – 7,245, SJIF – 5,431
ILMIY METODIK JURNAL
Foundation Medicine uses artificial intelligence to analyze genomic data. This system analyzes
patients' genetic information and offers individualized treatment strategies. For example, by
determining the genetic profile of cancer patients, the SI system determines which drugs will be
most effective.
IBM Watson for Oncology is an artificial intelligence-based system that helps oncologists
develop treatment plans. The system analyzes patients’ medical histories, laboratory results, and
imaging to provide personalized treatment recommendations. Studies show that Watson for
Oncology supports doctors’ decisions in many cases and provides recommendations based on
updated scientific evidence.
The use of artificial intelligence (AI) in medicine opens up many possibilities, but this process
also involves ethical and legal aspects. Below are some thoughts on these aspects and future
development prospects.
AI systems collect a lot of data, including patients’ personal and medical histories. The
protection and confidentiality of this data are important. Patients need to know how their data
will be used and give permission.
AI systems can provide diagnosis and treatment recommendations, but there is a risk of reducing
the role of doctors. It is important for doctors to retain their expertise and ability to communicate
with patients.
AI systems can sometimes make unfair decisions for certain groups or demographics. The
systems operate on the data they are trained on, and if that data is inaccurate or biased, so can the
results. This is an important issue for ensuring fairness and equity.
Who is liable if an AI system makes an incorrect diagnosis or treatment recommendation? The
doctor, the manufacturer, or the software company? This question is also important from a legal
perspective.
All countries have laws aimed at protecting personal data (for example, the GDPR in the
European Union). When using AI in medicine, these laws must be observed.
Diagnoses and recommendations made with the help of AI should be legally accepted. How will
patients’ rights be protected if the AI system makes an incorrect diagnosis? These issues need to
be clearly defined.
Algorithms and models that affect the operation of AI systems can be patented. This can create
problems for the development of innovations.
In the future, AI systems will work in closer cooperation with doctors. The goal of this
cooperation is to provide patients with better quality and individualized care.
AI systems must be constantly updated and trained with new data. This will increase their
accuracy and allow them to identify new diseases.
It is necessary to develop ethical standards and legislation for the use of AI. This will increase
the efficiency of AI systems, while protecting patients’ rights.
JOURNAL OF IQRO – ЖУРНАЛ ИҚРО – IQRO JURNALI – volume 16, issue 02, 2025
ISSN: 2181-4341, IMPACT FACTOR ( RESEARCH BIB ) – 7,245, SJIF – 5,431
ILMIY METODIK JURNAL
AI technologies are also developing in the field of telemedicine. They allow for more efficient
remote diagnosis and treatment processes.
Conclusion.
In conclusion, artificial intelligence (AI) is an important tool that is revolutionizing
medical diagnostics, increasing accuracy, efficiency, and speed in this field. AI algorithms, with
their ability to analyze large amounts of data, help doctors make quick and accurate diagnoses.
They can be effective in detecting diseases at an early stage, developing individualized treatment
plans, and monitoring patients' condition. However, the use of AI also raises a number of ethical
and legal issues. Issues such as privacy, data protection, and responsibility between humans and
AI remain relevant. The impartiality and fair operation of AI systems are also important. In the
future, AI is expected to be used more widely in medicine. However, its success will depend on
the cooperation between doctors and technology, the development of ethical standards, and
legislation. In general, the process of medical diagnostics using AI not only provides innovative
approaches, but also creates the opportunity to provide better and more efficient services for
patients.
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