[Application of deep learning in cancer prognosis prediction model].

In recent years, deep learning has provided a new method for cancer prognosis analysis. The literatures related to the application of deep learning in the prognosis of cancer are summarized and their advantages and disadvantages are analyzed, which can be provided for in-depth research. Based on this, this paper systematically reviewed the latest research progress of deep learning in the construction of cancer prognosis model, and made an analysis on the strengths and weaknesses of relevant methods. Firstly, the construction idea and performance evaluation index of deep learning cancer prognosis model were clarified. Secondly, the basic network structure was introduced, and the data type, data amount, and specific network structures and their merits and demerits were discussed. Then, the mainstream method of establishing deep learning cancer prognosis model was verified and the experimental results were analyzed. Finally, the challenges and future research directions in this field were summarized and expected. Compared with the previous models, the deep learning cancer prognosis model can better improve the prognosis prediction ability of cancer patients. In the future, we should continue to explore the research of deep learning in cancer recurrence rate, cancer treatment program and drug efficacy evaluation, and fully explore the application value and potential of deep learning in cancer prognosis model, so as to establish an efficient and accurate cancer prognosis model and realize the goal of precision medicine.

Cloud-based digital healthcare development for precision medical hospital information system.

Aim: This study aims to develop a cloud-based digital healthcare system for precision medical hospital information systems (P-HIS). Methods: In 2020, international standardization of P-HIS clinical terms and codes was performed. In 2021, South Korea's first tertiary hospital cloud was established and implemented successfully. Results: P-HIS was applied at Korea's first tertiary general hospital. Common data model-compatible precision medicine/medical service solutions were developed for medical support. Ultrahigh-quality medical data for precision medicine were acquired and built using big data. Joint global commercialization and dissemination/spreading were achieved using the P-HIS consortium and global common data model-based observational medical outcome partnership network. Conclusion: To provide personalized precision medical services in the future, establishing and using big medical data is essential.

Nondimensional diabetes indices for accurate diagnosis of diabetic subjects.

OBJECTIVES: Nondimensional indices or numbers can provide a generalized approach for integrating several biological parameters into one Nondimensional Physiological Index (NDPI) that can help characterize an abnormal state associated with a particular physiological system. In this paper, we have presented four Nondimensional Physiological Indices (NDI, DBI, DIN, CGMDI) for the accurate detection of diabetes subjects. METHODOLOGY: The NDI, DBI, and DIN diabetes indices are based on the Glucose-Insulin Regulatory System (GIRS) Model, represented by the governing differential equation of blood glucose concentration response to the glucose input rate. The solutions of this governing differential equation are employed to simulate the clinical data of the Oral Glucose Tolerance Test (OGTT), and thereby evaluate the GIRS model-system parameters, which are distinctly different for the normal and diabetic subjects. Then these GIRS model parameters are combined to form singular nondimensional indices: NDI, DBI, and DIN. When these indices are applied to the OGTT clinical data, we get significantly different values for normal and diabetic subjects. The DIN diabetes index is a more objective index involving extensive clinical studies, incorporating the GIRS model parameters as well as some key clinical-data markers (based on the information gained from the model clinical simulation and parametric identification). We have then developed another CGMDI diabetes index based on the GIRS model, for the assessment of diabetic subjects using the glucose levels measured by wearable continuous glucose monitoring (CGM) devices. CLINICAL STUDY AND RESULTS: For the DIN diabetes index, our clinical study comprised of 47 subjects (26 normal and 21 diabetics). After applying DIN to the OGTT data, a Distribution Plot of DIN was developed, displaying the ranges of DIN for (i) normal (i.e., non-diabetic) subjects with no risk of becoming diabetic, (ii) normal subjects at risk of becoming diabetic, (iii) borderline diabetic subjects who can become normal (with diet control and treatment), and (iv) distinctly diabetic subjects. This distribution plot is shown to distinctly separate normal subjects from diabetic subjects and also from subjects at risk of becoming diabetic. CONCLUSIONS: In this paper, we have developed several NDPIs in the form of novel nondimensional diabetes indices for the accurate detection of diabetes and diagnosis of diabetic subjects. These nondimensional diabetes indices can enable precision medical diagnostics of diabetes, and thereby also help to develop interventional guidelines for lowering glucose levels by means of insulin infusion. The novelty of our proposed CGMDI is that it utilizes the glucose value monitored by the CGM wearable device. In the future, an app can be developed to use the CGM data in the CGMDI to enable precision diabetes detection.

Impoverishment Effect of Hydatid Disease and Precision Medical Assistance Pattern of Government: Evidence from Yushu in China.

Hydatid disease is one of the 17 neglected tropical diseases recognized by WHO and causes a huge global disease burden. Hydatid disease poses a great threat to local medical poverty alleviation. In efforts to break the vicious circle of poverty, Hydatid disease has been widely concerned and discussed. In the practice of poverty alleviation in China, medical poverty alleviation is regarded as the double goal of getting rid of poverty and promoting the construction of a healthy China. On the basis of on-the-spot investigation in Yushu Prefecture, this paper conducts a follow up study on the poverty-causing effect of Hydatid disease and the precision medical assistance pattern of government using a field investigation method. The results show that Hydatid disease led to the increase of poverty in the population in Yushu Prefecture, precision medical assistance played an obvious role in treating Hydatid disease and poverty alleviation, the health service in the study area continues to improve and the medical backbone team further expanded. The main conclusion is that the three-level diagnosis and treatment framework can effectively reduce local poverty and improve people's living environment.

Pre-class online video learning and class style expectation: patterns, association, and precision medical education.

BACKGROUND: Online video learning has been gaining substantial attention in medical education. The purpose of the study was to evaluate medical students' online video-viewing patterns as well as to identify features associated with their class style preferences in precision medicine courses. METHODS: A mixed methods research design was used. Part of the cognitive load of the class content of "acute liver failure" was shifted to a 10-minute pre-class online video learning which was further reduced using threshold concept strategy. In the 2019 academic year, all fifth-year medical students who had viewed the pre-class video were invited to take a survey on their learning process and four class style expectations for the upcoming in-person class. For each round of medical students, teaching assistants helped collect anonymous survey data before the class. The teacher then adjusted the in-person class as part of precision medical education. Furthermore, the researchers coded the video-viewing patterns through an action log transformation, along with the questionnaire results, for analysis. Mann-Whitney U and Kruskal-Wallis tests were employed to compare group differences. Qualitative data were content-coded through a descriptive approach using thematic analysis. RESULTS: Of the 130 medical students, 114 (87.7%) joined the pre-class video learning, 113 (86.9%) responded to the questionnaires, and 87 (66.9%) provided their comments. Most medical students preferred the class styles of a thorough introduction (42.5%) and concept orientation (44.2%). High-engagement viewing patterns were associated with difficult concepts and the provision of comments. Class style expectation and video-viewing patterns did not demonstrate significant linkages. A majority of the substantial comments initiated thought-provoking questions after the online video learning. CONCLUSION: Association between medical students' preferred class styles and online video-viewing patterns was not necessarily linked. However, medical teachers are recommended to modify class styles based on medical students' expectations after pre-class learning, thereby providing precision medical education.KEY MESSAGEImplementing precision medical education in the blended class is feasible.Online video learning is an ideal platform for balancing the dilemma between increasing the cognitive load of class content and the practice of precision medical education.The association between medical students' preferred class styles and online video-viewing patterns was not clearly seen.

The importance of genetic counseling and genetic screening: a case report of a 16-year-old boy with resistant hypertension and severe hypokalemia.

Liddle's syndrome, an autosomal dominant form of monogenic hypertension, is characterized by salt-sensitive hypertension with early penetrance, hypokalemia, metabolic alkalosis, suppression of plasma rennin activity and aldosterone secretion, and a clear-cut response to epithelial sodium channel blockers but not spironolactone therapy. Here, we describe the case of a 16-year-old boy patient with resistant hypertension (maintain 170-180/100-110 mm Hg after administration four kinds of antiypertensive drugs) and severe hypokalemia. After a series of checks, we exclude primary aldosteronism and renal artery stenosis and other diseases. Finally, the Liddle syndrome was diagnosed because of the DNA sequencing found that the proband's mother and himself had mutations P616L (c.1847 C>T) in the SCNN1B gene. Liddle syndrome should be considered as a cause of hypertension in children or adolescents particularly with suppressed renin activity. Early diagnosis and appropriately tailored treatment avoid complications of long-term unrecognized or inappropriately managed hypertension. Genetic testing has made it possible to make accurate diagnoses and develop tailored therapies for mutation carriers. The role of genetic testing and genetic counseling in establishing the early diagnosis of Liddle's syndrome is important.

Design and Fabrication of a Precision Template for Spine Surgery Using Selective Laser Melting (SLM).

In order to meet the clinical requirements of spine surgery, this paper proposes the fabrication of the customized template for spine surgery through computer-aided design. A 3D metal printing-selective laser melting (SLM) technique was employed to directly fabricate the 316L stainless steel template, and the metal template with tiny locating holes was used as an auxiliary tool to insert spinal screws inside the patient's body. To guarantee accurate fabrication of the template for cervical vertebra operation, the contact face was placed upwards to improve the joint quality between the template and the cervical vertebra. The joint surface of the printed template had a roughness of Ra = 13 ± 2 µm. After abrasive blasting, the surface roughness was Ra = 7 ± 0.5 µm. The surgical metal template was bound with the 3D-printed Acrylonitrile Butadiene Styrene (ABS) plastic model. The micro-hardness values determined at the cross-sections of SLM-processed samples varied from HV0.3 250 to HV0.3 280, and the measured tensile strength was in the range of 450 MPa to 560 MPa, which showed that the template had requisite strength. Finally, the metal template was clinically used in the patient's surgical operation, and the screws were inserted precisely as the result of using the auxiliary template. The geometrical parameters of the template hole (e.g., diameter and wall thickness) were optimized, and measures were taken to optimize the key geometrical units (e.g., hole units) in metal 3D printing. Compared to the traditional technology of screw insertion, the use of the surgical metal template enabled the screws to be inserted more easily and accurately during spinal surgery. However, the design of the high-quality template should fully take into account the clinical demands of surgeons, as well as the advice of the designing engineers and operating technicians.

Application of deep learning in cancer prognosis prediction model / 生物医学工程学杂志

In recent years, deep learning has provided a new method for cancer prognosis analysis. The literatures related to the application of deep learning in the prognosis of cancer are summarized and their advantages and disadvantages are analyzed, which can be provided for in-depth research. Based on this, this paper systematically reviewed the latest research progress of deep learning in the construction of cancer prognosis model, and made an analysis on the strengths and weaknesses of relevant methods. Firstly, the construction idea and performance evaluation index of deep learning cancer prognosis model were clarified. Secondly, the basic network structure was introduced, and the data type, data amount, and specific network structures and their merits and demerits were discussed. Then, the mainstream method of establishing deep learning cancer prognosis model was verified and the experimental results were analyzed. Finally, the challenges and future research directions in this field were summarized and expected. Compared with the previous models, the deep learning cancer prognosis model can better improve the prognosis prediction ability of cancer patients. In the future, we should continue to explore the research of deep learning in cancer recurrence rate, cancer treatment program and drug efficacy evaluation, and fully explore the application value and potential of deep learning in cancer prognosis model, so as to establish an efficient and accurate cancer prognosis model and realize the goal of precision medicine.

The application of 3D printing in ophthalmology / 中华实验眼科杂志

3D printing refers to the approach in manufacturing the three-dimensional physical objects by adding materials layer by layer.It features the advantages of quick styling, high flexibility and cost saving.The medical industry is extensively regarded as one of the most important application sectors for 3D printing.In recent years, due to the development of technical and the enhanced support from the nation in the 3D related research, the application of 3D printing technology in the ophthalmology has been increasing.This review made the overview analysis on the 3D printing technology application and possible prospects in the aspects of medical education, foundation research, surgical assistance and individualized treatment of ophthalmology, made a brief introduction on the 3D bioprinting technology attracting extensive attention recently.