This comprehensive review systematically explores the multifaceted applications, inherent challenges, and promising future directions of artificial intelligence (AI) within the medical domain. It meticulously examines AI's specific contributions to basic medical research, disease prevention, intelligent diagnosis, treatment, rehabilitation, nursing, and health management. Furthermore, the review delves into AI's innovative practices and pivotal roles in clinical trials, hospital administration, medical education, as well as the realms of medical ethics and policy formulation. Notably, the review identifies several key challenges confronting AI in healthcare, encompassing issues such as inadequate algorithm transparency, data privacy concerns, absent regulatory standards, and incomplete risk assessment frameworks. Looking ahead, the future trajectory of AI in healthcare encompasses enhancing algorithm interpretability, propelling generative AI applications, establishing robust data-sharing mechanisms, refining regulatory policies and standards, nurturing interdisciplinary talent, fostering collaboration among industry, academia, and medical institutions, and advancing inclusive, personalized precision medicine. Emphasizing the synergy between AI and emerging technologies like 5G, big data, and cloud computing, this review anticipates a new era of intelligent collaboration and inclusive sharing in healthcare. Through a multidimensional analysis, it presents a holistic overview of AI's medical applications and development prospects, catering to researchers, practitioners, and policymakers in the healthcare sector. Ultimately, this review aims to catalyze the deep integration and innovative deployment of AI technology in healthcare, thereby driving the sustainable advancement of smart healthcare.

This article systematically analyzes the historical evolution of the name， origin， quality evaluation， harvesting， processing and other aspects of Picrorhizae Rhizoma by referring to the medical books， prescription books， and other documents of the past dynasties， combined with relevant modern research materials， in order to provide a basis for the development and utilization of famous classical formulas containing this medicinal herb. The research results indicate that Picrorhizae Rhizoma was first recorded in New Revised Materia Medica from the Tang dynasty. Throughout history， Huhuanglian has been used as its official name， and there are also aliases such as Gehu Luze， Jiahuanglian and Hulian. The main source of past dynasties is the the rhizomes of Picrorhiza kurrooa and P. scrophulariiflora. In ancient times， Picrorhizae Rhizoma was mainly imported by foreign traders via Guangzhou and other regions， and also produced in China， mainly in Xizang. In ancient times， it was harvested and dried in early August of the lunar calendar， while in modern times， it is mostly harvested from July to September， with the best quality being those with thick and crispy rhizomes without impurities， and bitter taste. Throughout history， Picrorhizae Rhizoma was collected， washed， sliced， and dried before being used as a raw material for medicine， it has a bitter and cold taste， mainly used to treat bone steaming， hot flashes， infantile chancre fever， and dysentery. There is no significant difference in taste and efficacy between ancient and modern times. Based on the research results， it is recommended that the rhizomes of P. scrophulariiflora in the 2020 edition of Chinese Pharmacopoeia， or the rhizomes of P. kurrooa， can be used in famous classical formulas containing this medicinal herb， which can be processed according to the processing requirements marked by the original formula. For those without clear processing requirements， the dried raw products are used as medicine.

Objective To evaluate the reporting quality and influencing factors of patient-reported outcome (PRO) data in randomized controlled trials (RCTs) of lung cancer. Methods RCTs of lung cancer with PRO as either primary or secondary endpoints were searched from PubMed, EMbase, Medline, CNKI, Wanfang Data, and VIP databases between January 1, 2010 and April 20, 2024. Reporting quality of included RCTs were assessed based on the CONSORT-PRO extension. Descriptive statistics and bivariate regression analysis were used to describe the reporting quality and analyze the factors influencing the reporting quality. Results A total of 740 articles were retrieved. After screening, 53 eligible RCTs of lung cancer with 22 780 patients were included. The patients were mainly with non-small cell lung cancer (84.91%), with the median sample size of the included studies was 364.0 (160.5, 599.5) patients. The primary PRO tool used was the EORTC QLQ-C30 (60.38%). There were 52 (98.11%) studies whose PRO measured the domain of "symptom management of cough, dyspnea, fatigue, pain, etc.", and 45 (84.91%) studies measured "health-related quality of life". Multicenter studies accounted for 84.91%, and randomized non-blind trials accounted for 62.26%. PRO was used as the primary endpoint in 33.96% of the studies and as secondary endpoints in 66.04%. The reliability and validity of the PRO tools were explicitly mentioned in 11.32% and 7.55% of the studies, respectively. The average completeness of reporting according to the CONSORT-PRO guidelines was 60.00%, ranging from 25.00% to 93.00%. The main factors affecting the completeness of CONSORT-PRO reporting included sample size and publication year. For every increment in sample size, the completeness of reporting increased by 27.5% (SE=0.00, t=2.040, P=0.046). Additionally, studies published after 2018 had a 67.2% higher completeness of reporting compared to those published in or before 2018 (SE=17.8, t=–3.273, P=0.006). Conclusion The study reveals that the overall reporting quality of PRO in lung cancer RCTs is poor. Particularly, the reporting of PRO measures reliability and validity, PRO assumptions, applicability, and handling of missing data need further improvement. Future research should emphasize comprehensive adherence to the CONSORT-PRO guidelines.

The immunomodulatory， repair， and regeneration-promoting functions of mesenchymal stem cells make them one of the potential treatment methods for liver diseases. At present， viral and non-viral delivery methods have been developed to genetically modify mesenchymal stem cells， and gene modification can promote the survival， homing， and cytokine secretion of mesenchymal stem cells， thereby enhancing the ability of mesenchymal stem cells to treat liver diseases. This article mainly summarizes the research advances in gene-modified mesenchymal stem cells in the treatment of liver diseases， in order to provide new insights and strategies for the clinical treatment of liver diseases.

The Consolidated Standards of Reporting Trials (CONSORT) statement aims to enhance the quality of reporting for randomized controlled trial (RCT) by providing a minimum item checklist. It was first published in 1996, and updated in 2001 and 2010, respectively. The latest version was released in April 2025, continuously reflecting new evidence, methodological advancements, and user feedback. CONSORT 2025 includes 30 essential checklist items and a template for a participant flow diagram. The main changes to the checklist include the addition of 7 items, revision of 3 items, and deletion of 1 item, as well as the integration of multiple key extensions. This article provides a comprehensive interpretation of the statement, aiming to help clinical trial staff, journal editors, and reviewers fully understand the essence of CONSORT 2025, correctly apply it in writing RCT reports and evaluating RCT quality, and provide guidance for conducting high-level RCT research in China.

As the volume of medical research using large language models (LLM) surges, the need for standardized and transparent reporting standards becomes increasingly critical. In January 2025, Nature Medicine published statement titled by TRIPOD-LLM reporting guideline for studies using large language models. This represents the first comprehensive reporting framework specifically tailored for studies that develop prediction models based on LLM. It comprises a checklist with 19 main items (encompassing 50 sub-items), a flowchart, and an abstract checklist (containing 12 items). This article provides an interpretation of TRIPOD-LLM’s development methods, primary content, scope, and the specific details of its items. The goal is to help researchers, clinicians, editors, and healthcare decision-makers to deeply understand and correctly apply TRIPOD-LLM, thereby improving the quality and transparency of LLM medical research reporting and promoting the standardized and ethical integration of LLM into healthcare.

OBJECTIVE To establish a method for the content determination of 11 components such as protodioscin in Guge fengtong tablets， and to evaluate the comprehensive quality of Guge fengtong tablets by combining with chemometric analysis and entropy weight-technique for order preference by similarity to ideal solution （EW-TOPSIS） method. METHODS HPLC method was adopted. The determination was performed on Agilent Eclipse Plus C18 column with a mobile phase consisted of acetonitrile- 0.2% phosphoric acid solution at the flow rate of 1.0 mL/min by gradient elution. The column temperature was set at 30 ℃ . The detection wavelengths were set at 203 nm （0-28 min， protodioscin， methyl protodioscin， pseudoprotodioscin， dioscin） and 280 nm （28-60 min， catechin， epicatechin， liquiritigenin， medicarpin， 6-gingerol， 8-gingerol， 10-gingerol）； the sample size was 10 μL. Using epicatechin as the internal reference， quantitative analysis of multi-components by single marker （QAMS） method was used to determine the contents of protodioscin， methyl protodioscin， pseudoprotodioscin， dioscin， catechin， liquiritigenin， medicarpin， 6-gingerol， 8-gingerol and 10-gingerol， which were compared with the results of the external standard method. SPSS 26.0 software and SIMCA 14.1 software were used for principal component analysis and orthogonal partial least squares-discriminant analysis， with variable importance in projection （VIP） value greater than 1 as the standard， to screen for differential markers that affect the quality； the EW-TOPSIS method was adopted to evaluate the quality of 15 batches of samples comprehensively.RESULTS The contents of protodioscin， methyl protodioscin， pseudoprotodioscin， dioscin， catechin， liquiritigenin， medi-carpin， 6-gingerol， 8-gingerol and 10-gingerol determined by HPLC combined with QAMS were 6.330-10.863， 1.150-2.274， 0.431- 0.740， 2.818-4.823， 0.826-1.510， 0.043-0.094， 0.079-0.231， 0.479-1.020， 0.146-0.288， 0.118-0.318 mg/g， respectively； there were no statistical significances， compared with the external standard method （P＞0.05）. A total of 15 batches of samples were clustered into 3 groups， with S1-S6， S7-S10， and S11-S15 clustered into one group， respectively. The VIP values of protodioscin， epicatechin， dioscin and 6-gingerol were greater than 1. Euclidean closeness values of the optimal solution （C）i for 15 batches of samples were 0.163 5 to 0.703 7， and Ci values of S11-S15 were all higher than 0.6. CONCLUSIONS The established QAMS method is accurate and simple， and can be used for comprehensive quality evaluation of Guge fengtong tablets， by combining with chemometric analysis and EW-TOPSIS method. Protodioscin， epicatechin， dioscin and 6-gingerol are the differential markers that affect the quality of Guge fengtong tablets. Samples S11-S15 have better quality.

Objective To compare the diagnostic value of smear acid-fast staining,TB-DNA,X-pert MTB/RIF and culture of Mycobacterium tuberculosis.Methods Four methods were used to detect the perifocal pus of the patients with bone destruction in orthopaedics department within one year,and the results were analyzed statistically,the indexes included sensitivity,specificity,positive predictive value and negative predictive value.Results The sensitivity,specificity,positive predictive value,negative predictive value,and Youden index were 31.75%,100.00%,100.00%,53.74%and 0.32 respectively.TB-DNA had a sensitivity of 88.89%,a specificity of 98.00%,a positive predictive value of 98.25%,a negative predictive value of 87.50%,and a Youden Index of 0.87.Xpert MTB/Rif had a sensitivity of 95.23%,a specificity of 68.00%,and a positive predictive value of 78.95%,the negative predictive value was 91.90%,the Youden index was 0.63.The sensitivity,the specificity,the positive predictive value,the negative predictive value and the Youden index were 41.27%,100.00%,100.00%,57.47%and 0.41 respectively,(χ2 = 77.354,P<0.005).Conclusion Among the four methods,TB-DNA has a good Sensitivity and specificity,Xpert mtbrif has a good sensitivity,TB-DNA and Xpert mtbrif ha a good authenticity,and both positive and negative predictive values are high,it has good value in the diagnosis of bone tuberculosis.

Objective:To investigate the prediction of the tumor proliferation antigen(Ki-67) expression status in breast cancer patients based on ultrasound radiomics combined with clinicopathologic features.Methods:Breast cancer patients who underwent 2D ultrasound and Ki-67 examination from January 2018 to February 2022 in Changzhou Second People′s Hospital, Nanjing Medical University were retrospectively analyzed. Among them, 427 patients from Chengzhong campus were randomly divided into training and validation sets in the ratio of 8∶2, and 229 patients from Yanghu campus were used as an independent external test set. Radiomics features were extracted from the region of interest of 2D ultrasound images, and the Mann-Whitney U test, recursive feature elimination, and minimum absolute shrinkage and selection operators were used to perform feature dimensionality reduction and to establish a radiomics score(Rad-score). Subsequently, single/multifactor logistic regression regression analyses were used to construct a joint prediction model based on Rad-score and clinicopathological features. Model performance and utility were assessed using the subject operating characteristic area under the curve (AUC), calibration curve, and decision curve analyses. Results:The AUCs of the joint model for predicting Ki-67 expression status in breast cancer in the training, validation, and test sets were 0.858, 0.797, and 0.802, respectively, which were superior to those of the radiomics (0.772, 0.731, and 0.713) and clinical models (0.738, 0.750, and 0.707). Calibration curve and decision curve analyses indicated that the joint model had good calibration and clinical value.Conclusions:A joint model based on ultrasound radiomics and clinicopathological features can effectively predict the Ki-67 expression status of breast cancer, which is expected to become a non-invasive tool for Ki-67 detection and provide clinicians with an important auxiliary diagnostic and therapeutic decision-making basis.

ObjectiveTo explore the distribution characteristics of traditional Chinese medicine （TCM） syndrome elements of macroangiopathy in patients with type 2 diabetes mellitus （T2DM） and the key elements of occurrence， development and progression of disease. MethodsA multicenter cross-sectional study was conducted to enroll 445 T2DM patients from five hospitals， and according to the presence or absence of macroangiopathy， the patients were divided into a T2DM group （120 cases） and a diabetic macroangiopathy （DM） group （325 cases）. Patients in DM group were divided into grade Ⅰ， Ⅱ， Ⅲ and Ⅳ according to the peripheral vascular color Doppler ultrasound results and the vascular anomalies classification standard. The general data including gender， age， duration of T2DM and body mass index （BMI） were collected， and the data of four examinations were obtained for syndrome differentiation. According to the diagnostic criteria of TCM syndrome elements， the patients can be divided into 9 patterns including qi deficiency， blood deficiency， yin deficiency， yang deficiency， qi stagnation， blood stasis， excess heat， and excess cold. The general data and distribution of TCM syndrome elements were compared between the two groups. The distribution of TCM syndrome elements in different vascular anomalies grades in the DM group was analyzed. Logistic regression analysis was used to explore the influence of various TCM syndrome elements on the occurrence of macroangiopathy in T2DM. ResultsThere was no significant difference in gender and BMI between groups （P＞0.05）. The age and duration of diabetes in the DM group were older and longer than those in the T2DM group （P＜0.01）. With the increase of age and prolonged course of disease， the severity of diabetic macroangiopathy increases gradually （P＜0.05 or P＜0.01）. There was no significant difference in BMI and course of disease among the different TCM syndrome elements （P＞0.05）. The average age of patients with blood stasis syndrome was the oldest （P＜0.05）. There was significant difference in gender distribution between the excess heat syndrome and yin deficiency syndrome （P＜0.05）. A total of 240 TCM syndrome elements were extracted from the T2DM group， while 731 TCM syndrome elements extracted from the DM group. The top two high-frequency syndrome elements in the two groups were qi deficiency and yin deficiency， with a frequency of larger than 50%. The distribution of phlegm-damp syndrome and blood-stasis syndrome were significantly higher in the DM group than in the T2DM group （P＜0.01）. There were significant differences in the distribution of qi deficiency syndrome， yin deficiency syndrome， phlegm-damp syndrome， blood stasis syndrome， and excess heat syndrome among different grades of vascular anomalies （P＜0.01）； qi deficiency and yin deficiency were both high-frequency TCM syndrome elements in patients at grades 0 to Ⅲ； phlegm-damp syndrome increased in frequency with the progression of the disease from grades 0 to Ⅳ， and the frequency of blood stasis syndrome showed an overall upward trend. The frequency of phlegm-dampness syndrome increased from grades 0 to Ⅳ with the progression of the disease， and the frequency of blood stasis syndrome showed an overall upward trend. Logistic regression analysis showed that phlegm-damp syndrome and blood stasis syndrome were important TCM syndrome elements related to the vascular anomalies degree of macrovascular disease in T2DM （P＜0.05 or P＜0.01）. ConclusionQi deficiency and yin deficiency are the basic TCM syndrome elements throughout the whole process of T2DM and diabetic macrovascular disease. Phlegm-damp and blood stasis are related to the degree of vascular anomalies in diabetic macrovascular disease and are the key TCM syndrome elements in the progression of macroangiopathy in T2DM.