Thyroid cancer is the most common malignant tumor of the endocrine system,and its incidence has been steadily increasing in recent years. Papillary thyroid carcinoma (PTC) and follicular thyroid carcinoma (FTC),collectively known as differentiated thyroid cancer (DTC),account for approximately 95％ of thyroid cancer cases. Imaging examinations such as ultrasound,computed tomography (CT),magnetic resonance imaging (MRI),single-photon emission computed tomography (SPECT/CT),and positron emission tomography (PET/CT) play a critical role in the diagnosis,staging,risk stratification,and treatment of DTC. However,the analysis of imaging results heavily depends on the skills and experience of the physician,making the interpretation prone to errors due to factors such as image volume,complexity,and subjective judgment,particularly under high workloads. Additionally,objective factors like equipment resolution and the limitations of human vision can also affect diagnostic accuracy. Artificial intelligence (AI),a technology that simulates,extends,and enhances human intelligence,has gradually been applied in the medical field. In the diagnosis and treatment of DTC,AI technologies such as machine learning and deep learning,as well as radiomics,have been utilized. These technologies are primarily applied in the diagnosis and differential diagnosis of DTC,staging assessments,prediction of genetic mutations,and iodine-131 therapy for DTC. The application of AI and radiomics holds great promise for improving diagnostic accuracy,enabling precise staging,predicting genetic mutations with higher precision,and optimizing treatment strategies for DTC. This advancement is expected to facilitate accurate diagnosis and personalized treatment,maximizing benefits for patients.

Inflammatory bowel disease (IBD) is a chronic idiopathic inflammatory intestinal disease that can affect the entire digestive tract, mainly including ulcerative colitis and Crohn's disease. Currently, the etiology and pathogenesis of IBD have not been fully elucidated and may be related to genetic susceptibility, environmental factors, abnormal immune response, impaired intestinal barrier, and imbalance of gut microbiota. With the advancement of high-throughput sequencing technology, the application of gut microbiome in precision medicine for IBD has become more extensive and in-depth. Utilizing the gut microbiome can enable earlier detection of disease signs, accurate prediction of disease development trends, and real-time monitoring of its progression, providing new possibilities for individualized treatment of IBD. This article reviews and summarizes the existing evidence of gut microbiome in the precise diagnosis and typing of IBD, monitoring disease progression, and predicting therapeutic effects, and also looks forward to the prospects of microbiome applications in precision medicine.

Inflammatory bowel disease (IBD) is a chronic idiopathic inflammatory intestinal disease that can affect the entire digestive tract, mainly including ulcerative colitis and Crohn's disease. Currently, the etiology and pathogenesis of IBD have not been fully elucidated and may be related to genetic susceptibility, environmental factors, abnormal immune response, impaired intestinal barrier, and imbalance of gut microbiota. With the advancement of high-throughput sequencing technology, the application of gut microbiome in precision medicine for IBD has become more extensive and in-depth. Utilizing the gut microbiome can enable earlier detection of disease signs, accurate prediction of disease development trends, and real-time monitoring of its progression, providing new possibilities for individualized treatment of IBD. This article reviews and summarizes the existing evidence of gut microbiome in the precise diagnosis and typing of IBD, monitoring disease progression, and predicting therapeutic effects, and also looks forward to the prospects of microbiome applications in precision medicine.

Thyroid cancer is the most common malignant tumor of the endocrine system,and its incidence has been steadily increasing in recent years. Papillary thyroid carcinoma (PTC) and follicular thyroid carcinoma (FTC),collectively known as differentiated thyroid cancer (DTC),account for approximately 95％ of thyroid cancer cases. Imaging examinations such as ultrasound,computed tomography (CT),magnetic resonance imaging (MRI),single-photon emission computed tomography (SPECT/CT),and positron emission tomography (PET/CT) play a critical role in the diagnosis,staging,risk stratification,and treatment of DTC. However,the analysis of imaging results heavily depends on the skills and experience of the physician,making the interpretation prone to errors due to factors such as image volume,complexity,and subjective judgment,particularly under high workloads. Additionally,objective factors like equipment resolution and the limitations of human vision can also affect diagnostic accuracy. Artificial intelligence (AI),a technology that simulates,extends,and enhances human intelligence,has gradually been applied in the medical field. In the diagnosis and treatment of DTC,AI technologies such as machine learning and deep learning,as well as radiomics,have been utilized. These technologies are primarily applied in the diagnosis and differential diagnosis of DTC,staging assessments,prediction of genetic mutations,and iodine-131 therapy for DTC. The application of AI and radiomics holds great promise for improving diagnostic accuracy,enabling precise staging,predicting genetic mutations with higher precision,and optimizing treatment strategies for DTC. This advancement is expected to facilitate accurate diagnosis and personalized treatment,maximizing benefits for patients.

Amyloidosis is a local or systemic disease caused by the deposition of misfolded proteins outside the cell,with rapid progression,and dire prognosis.Common types of cardiac amyloidosis are monoclonal immunoglobulin light chain amyloidosis(AL-CA)and transthyretin cardiac amyloidosis(ATTR-CA).Nuclear medicine examinations can be accurate,rapid,and non-invasive to help diagnose diseases and can effectively predict the prognosis of patients with CA.Technetium(99Tcm)-labeled bisphosphonate imaging has been included in the consensus of experts and has become the first-line imaging method for the diagnosis of ATTR-CA.123I-metaiodoenzylguanidine(MIBG)as a norepinephrine analogue can effectively assess cardiac sympathetic innervation in patients with CA.Aβ-amyloid imaging agents such as 11C-pittsburgh compound B and 18F-flubetaben are expected to be new techniques for diagnosing AL-CA and incorporating them into cardiac staging systems for AL-CA patients in the future.New imaging agents such as 18F-NaF has been widely used in the diagnosis,treatment response monitoring,and prognosis assessment of CA.Summarizing the research value of nuclide imaging in CA may provide new ideas for clinical realization of early detection of CA and accurate assessment of disease prognosis.