Systematic Review of Health Economic Evaluations Focused on Artificial Intelligence in Healthcare: The Tortoise and the Cheetah

ObjectivesThis study aimed to systematically review recent health economic evaluations (HEEs) of artificial intelligence (AI) applications in healthcare. The aim was to discuss pertinent methods, reporting quality and challenges for future implementation of AI in healthcare, and additionally advise future HEEs.MethodsA systematic literature review was conducted in 2 databases (PubMed and Scopus) for articles published in the last 5 years. Two reviewers performed independent screening, full-text inclusion, data extraction, and appraisal. The Consolidated Health Economic Evaluation Reporting Standards and Philips checklist were used for the quality assessment of included studies.ResultsA total of 884 unique studies were identified; 20 were included for full-text review, covering a wide range of medical specialties and care pathway phases. The most commonly evaluated type of AI was automated medical image analysis models (n = 9, 45%). The prevailing health economic analysis was cost minimization (n = 8, 40%) with the costs saved per case as preferred outcome measure. A total of 9 studies (45%) reported model-based HEEs, 4 of which applied a time horizon >1 year. The evidence supporting the chosen analytical methods, assessment of uncertainty, and model structures was underreported. The reporting quality of the articles was moderate as on average studies reported on 66% of Consolidated Health Economic Evaluation Reporting Standards items.ConclusionsHEEs of AI in healthcare are limited and often focus on costs rather than health impact. Surprisingly, model-based long-term evaluations are just as uncommon as model-based short-term evaluations. Consequently, insight into the actual benefits offered by AI is lagging behind current technological developments.     

Bench to bedside: recent advances in lung cancer pathological research with implications for diagnostic clinical practice

After decades of relative stagnation lung cancer is emerging as a disease type where rapid progress is being made in diagnosis and therapy, as well as in our understanding of disease biology. Much of this progress is of immediate impact to diagnosticians, and more is likely to affect diagnostic practice in the near future. In this review we seek to briefly summarize several key areas of active research of immediate or probable imminent value to trainee and consultant pulmonary pathologists alike. We cover some major changes in tumour classification, grading, and patient stratification, as well as considering the state of the art in machine-assisted interpretation of lung cancer histology, and the use of genetically modified lung cancer models.     

近端胃切除人工三角瓣成形抗反流术的力学机理仿真分析

目的:对食管胃结合部腺癌近端胃切除术（PG）人工三角瓣成形后残胃食糜进行流体动力学数值模拟，并计算不同性质胃内食糜的流动特征。方法:构建常规PG和人工三角瓣成形术术后胃仿真模型，运用Fluent软件对不同粘度胃内食糜反流问题进行数值模拟。结果:站立位姿态时，相对常规PG方案，人工三角瓣成形手术方案表现出较好的抗反流作用；卧位姿态时，当胃内食糜粘度大于0.145 2 Pa[?s，且胃内食糜不超过人工三角瓣情况下，人工三角瓣成形抗反流手术表现出较好的抗反流效果；人工三角瓣抗反流成形手术方案数值模拟结果与临床上患者表现一致。结论:本研究仿真分析为人工三角瓣成形抗反流手术方案的有效性机理分析、临床患者术后饮食及手术方案的进一步改进提供理论及数值依据。 【关键词】食管胃结合部腺癌；抗反流；人工三角瓣；计算流体力学     

In silico repurposing the Rac1 inhibitor NSC23766 for treating PTTG1-high expressing clear cell renal carcinoma

The pituitary tumor-transforming gene 1 (PTTG1), also known as Securin, is considered an oncogene. This study aimed to investigate the role of PTTG1 in clear cell renal cell carcinoma (ccRCC) using in silico bioinformatics approaches. A pan-cancer analysis using The Cancer Genome Atlas (TCGA) data indicated that among all cancer types copy number amplification of PTTG1 gene was most frequently found in ccRCC. However, amplification of PTTG1 gene copy number did not correlate with the increase of mRNA level in ccRCC, and did not predict the patients' overall survival. Instead, ccRCC was correlated with overexpression of PTTG1 mRNA, and its expression level was stage-dependent increased in cancer patients. An outlier analysis using the Oncomine database suggested that PTTG1 mRNA expression served as a good biomarker for ccRCC. Pathway analysis for upregulated genes enriched in PTTG1-high expressing ccRCC patients found that PTTG1 overexpression was associated with mitotic defects. Mining drug sensitivity data using the Cancer Therapeutics Response Portal (CTRP) discovered that PTTG1-high expressing ccRCC cell lines were susceptible to a Rac1 (Ras-related C3 botulinum toxin substrate 1) inhibitor NSC23766. Therefore, this study provides an in silico insight into the role of PTTG1 in ccRCC, and repurposes the Rac1 inhibitor NSC23766 for treating PTTG1-high expressing ccRCC.     

A Review of Machine Learning Techniques for Keratoconus Detection and Refractive Surgery Screening

ABSTRACT

Various machine learning techniques have been developed for keratoconus detection and refractive surgery screening. These techniques utilize inputs from a range of corneal imaging devices and are built with automated decision trees, support vector machines, and various types of neural networks. In general, these techniques demonstrate very good differentiation of normal and keratoconic eyes, as well as good differentiation of normal and form fruste keratoconus. However, it is difficult to directly compare these studies, as keratoconus represents a wide spectrum of disease. More importantly, no public dataset exists for research purposes. Despite these challenges, machine learning in keratoconus detection and refractive surgery screening is a burgeoning field of study, with significant potential for continued advancement as imaging devices and techniques become more sophisticated.     

接受供精人工授精夫妇生育压力和生活质量研究

目的：调查接受供精人工授精（AID）夫妇的生育压力与生活质量，了解生育压力和生活质量的关系，为这些夫妇进行心理和生活质量干预时提供理论依据。方法：采用患者夫妇一般情况调查表、生育压力量表（FPI量表）和生活质量量表（FertiQoL量表）对北京大学第三医院2018年5—9月生殖中心门诊就诊的129对准备接受AID助孕的夫妇进行横断面调查，比较夫妇双方生育压力和生活质量的差异，分析生育压力和生活质量之间的关系。结果：接受AID的女性患者FPI总分为（159.00±17.52）分，FertiQoL总分为（62.27±9.26）分；男性配偶FPI总得分为（153.91±19.96）分，男性配偶FertiQoL总分为（65.12±11.62）分。女性FPI总分高于男性（t=2.436，P=0.016），女性无子女压力维度得分高于男性（t=3.145，P=0.002）。男性FertiQol总分高于女性（t=-2.881，P=0.005），女性情感反应维度得分高于男性（t=3.681，P=0.000），男性身心关系维度得分高于女性（t=-11.401，P=0.000）。Pearson 相关分析结果显示，接受AID助孕的女性FPI总分及性压力、夫妻关系、父母角色需求压力三个维度与其生活质量呈负相关（P＜0.05），接受AID男性配偶FPI总分和社会压力、性压力、夫妻关系维度、父母角色需求压力这4个维度与其生活质量呈负相关（P＜0.05）。多重线性回归显示，生育压力、居住地、文化程度是影响接受AID助孕女性患者生活质量的重要影响因素（F=3.485，R2=0.168，P＜0.05），生育压力、文化程度、家庭月收入是影响接受AID助孕男性配偶生活质量的重要影响因素（F=4.390，R2=0.203，P＜0.01）。结论：接受AID女性患者生育压力高于男性配偶，生活质量低于男性配偶；生育压力是影响AID夫妇生活质量的重要因素，夫妇双方生育压力越大，生活质量越低。