Modern medicine — and oncology in particular — is on the verge of integrating artificial intelligence (AI) into routine clinical practice. This article highlights some of the most successful initiatives showcasing how AI is being applied in diagnosing and predicting the progression of cancer. Existing clinical decision support systems that incorporate neural network-based oncology diagnostic modules are examined. For the first time, the limitations of AI applications in oncology are discussed, along with strategies to address these challenges.
| Mualliflar | Sobirov , Sherzod |
|---|---|
| Jurnal | Techscience.uz - техника фанлари долзарб масалалри |
| Nashr sanasi | 2025-08-11 |
| Jild | 3 |
| Son | 5 |
| Betlar | 5-10 |
| Til | Ingliz |
| DOI | 10.47390/ts-v3i5y2025n1 |
DOI: 10.47390/ts-v3i5y2025n1 · Maqolaning asl sahifasi
artificial intelligence, early diagnosis, genetic markers, clinical decision support systems, bioinformatics, machine learning, personalized therapy, sun’iy intellekt, erta diagnostika, genetik markerlar, klinik qaror qabul qilish tizimlari, bioinformatika, mashinali o‘qitish, personallashtirilgan terapiya
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