The potential of artificial intelligence (AI) to significantly transform numerous aspects of contemporary civilization is substantial. Advancements in research show an increasing interest in creating AI solutions in the healthcare sector. This interest is driven by the broad spectrum and extensive nature of easily accessible patient data‑including medical imaging, digitized data collection, and electronic health records ‑ and by the ability to analyze and interpret complex data, facilitating more accurate and timely diagnoses. This review's goal is to provide a comprehensive overview of the advancements achieved by AI in healthcare, to elucidate the present state of AI in enhancing the healthcare system and improving the quality and efficiency of healthcare decision making, and to discuss selected medical applications of AI. Furthermore, the barriers and constraints that may impede the use of AI in healthcare are outlined, and the potential future directions of AI‑augmented healthcare systems are discussed.

Anaplastic thyroid cancer (ATC) is a rare and aggressive form of thyroid malignancy, presenting significant challenges in diagnosis and treatment. The rarity of this cancer and its aggressive nature make an accurate diagnosis difficult, requiring a multidisciplinary approach and various imaging techniques. Treatment involves a personalized multimodal approach, including surgery, adjuvant therapies and risk stratification. Prognostic factors such as age, tumor characteristics and genetic alterations play a crucial role in determining patient outcomes. Despite advancements, gaps remain in understanding the underlying mechanisms of the disease and establishing standardized treatment guidelines. Further research, collaborative efforts and multicenter studies are necessary to improve diagnostic accuracy, develop targeted therapies and biomarkers, and enhance the long‑term management. The present review provides a comprehensive overview of ATC, discussing its clinical manifestations, diagnostic approaches, treatment options, prognostic factors and genetic landscape.

Biomarker discovery would be an important tool in advancing and utilizing the concept of precision and personalized medicine in the clinic. Discovery of novel variants in local population provides confident targets for developing biomarkers for personalized medicine. We identified the need to generate high-quality sequencing data from local colorectal cancer patients and understand the pattern of occurrence of variants. In this report, we used archived samples from Saudi Arabia and used the AmpliSeq comprehensive cancer panel to identify novel somatic variants. We report a comprehensive analysis of next-generation sequencing results with a coverage of >300X. We identified 466 novel variants which were previously unreported in COSMIC and ICGC databases. We analyzed the genes associated with these variants in terms of their frequency of occurrence, probable pathogenicity, and clinicopathological features. Among pathogenic somatic variants, 174 were identified for the first time in the large intestine. APC, RET, and EGFR genes were most frequently mutated. A higher number of variants were identified in the left colon. Occurrence of variants in ERBB2 was significantly correlated with those of EGFR and ATR genes. Network analyses of the identified genes provide functional perspective of the identified genes and suggest affected pathways and probable biomarker candidates. This report lays the ground work for biomarker discovery and identification of driver gene mutations in local population.

Woodhouse-Sakati syndrome (WSS) is a rare autosomal recessive multi-system genetic disease caused by loss of function mutations in the DCAF17 gene on chromosome 2q31.1. The disease is characterized by gradual neurologic degeneration and polyendocrinopathy, particularly noteworthy for hypogonadism, beginning in early adolescence. Clinical features show wide variability with no clear genotype-phenotype correlation. The pathophysiology of WSS is unclear at present and no specific treatment is available other than hormone replacement which is administered in the course of individualized symptomatic multidisciplinary care. Genetic testing helps in confirming the diagnosis along with genetic counseling of the patient and family members. Here we report multiple cases of WSS in three siblings from a new Saudi Arabia family who were diagnosed with WSS as a consequence of a common founder mutation in the DCAF17 gene with DNA analysis showing a homozygous single nucleotide frameshift deletion (c.436delC) in exon 4 of the gene.

Discovery of novel variants from data derived from local population provides confident targets for developing biomarkers for personalized medicine. Biomarker discovery would be an important tool in advancing and utilizing the concept of precision and personalized medicine in the clinic. We identified the need to generate high quality sequencing data from local population and understand the pattern of occurrence of variants in colorectal cancer patients. In this report, we used archived samples from Saudi Arabia and used Ampliseq Comprehensive Cancer panel to identify novel somatic variants. We report a comprehensive analysis of next generation sequencing results with a coverage of >300X. We identified 466 novel variants which were previously unreported in COSMIC and ICGC databases. We analyzed the genes associated with these variants in terms of their frequency of occurrence, probable pathogenicity and clinicopathological features. Among pathogenic somatic variants, 174 were identified for the first time in large intestine. APC, RET and EGFR genes were most frequently mutated. Higher number of variants were identified in left colon. Occurrence of variants in ERBB2 was significantly correlated with those of EGFR and ATR genes. Network analyses of the identified genes provide functional perspective of the identified genes and suggest affected pathways and probable biomarker candidates. This report lays the ground work for biomarker discovery and identification of driver gene mutations in local population.

Ewing’s sarcoma (EwS) is the second most common cancer that affects bone in children and adolescents. EwS is an aggressive malignancy with a projected overall survival of 70% for the low risk localized and 30% for the metastatic tumors. EwS is genetically described by its unique translocation that fuses FET family genes with the ETS family genes encoding transcription factors. The most frequent molecular event in over 90% of EwS cases is the translocation between EWSR1–FLI1. Additional events, ingincluding TP53, mutations, and CDKN2A deletions, have been reported but in low incidences. Hitherto, new research on EwS molecular processes is needed to lead to early diagnosis, disease monitoring, treatment development, improve patients’ survival, and quality of life. In this review, we outline the presently available information on the genetics underlying EwS carcinogenesis, investigate the existing understanding of the genetics underpinning EwS, and discuss the future directions for research on EwS.