Learning to screen Glaucoma like the ophthalmologists

GAMMA Challenge is organized to encourage the AI models to screen the glaucoma from a combination of 2D fundus image and 3D optical coherence tomography volume, like the ophthalmologists

Learning Personalized Risk Preferences for Recommendation

The rapid growth of e-commerce has made people accustomed to shopping online. Before making purchases on e-commerce websites, most consumers tend to rely on rating scores and review information to make purchase decisions. With this information, they can infer the quality of products to reduce the risk of purchase. Specifically, items with high rating scores and good reviews tend to be less risky, while items with low rating scores and bad reviews might be risky to purchase. On the other hand, the purchase behaviors will also be influenced by consumers' tolerance of risks, known as the risk attitudes. Economists have studied risk attitudes for decades. These studies reveal that people are not always rational enough when making decisions, and their risk attitudes may vary in different circumstances. Most existing works over recommendation systems do not consider users' risk attitudes in modeling, which may lead to inappropriate recommendations to users. For example, suggesting a risky item to a risk-averse person or a conservative item to a risk-seeking person may result in the reduction of user experience. In this paper, we propose a novel risk-aware recommendation framework that integrates machine learning and behavioral economics to uncover the risk mechanism behind users' purchasing behaviors. Concretely, we first develop statistical methods to estimate the risk distribution of each item and then draw the Nobel-award winning Prospect Theory into our model to learn how users choose from probabilistic alternatives that involve risks, where the probabilities of the outcomes are uncertain. Experiments on several e-commerce datasets demonstrate that our approach can achieve better performance than many classical recommendation approaches, and further analyses also verify the advantages of risk-aware recommendation beyond accuracy

Subcarinal ventilation-assisted Y-shaped stent insertion under local anesthesia for patients with complex tracheobronchial stenosis: initial clinical experience

PURPOSEWe aimed to report our preliminary results of subcarinal ventilation-assisted Y-shaped stent insertion under local anesthesia for patients with complex lower tracheal-carinal-main bronchial complex stenosis.MATERIALS AND METHODSSeven consecutive patients with lower tracheal-carinal-main bronchial complex stenosis underwent Y-shaped stent insertion under local anesthesia. During the procedure, subcarinal ventilation was performed using a 4 F angiographic catheter, and stent insertion was performed under the protection of ventilation. Data on technical success, clinical outcome, and follow-up were collected and analyzed.RESULTSSubcarinal ventilation-assisted Y-shaped stent insertion under local anesthesia was technically successful in all patients without any major procedure-related complications. Seven stents were inserted in seven patients. Respiratory function improved in all patients, with the Hugh-Jones classification of respiratory status improving from grade IV–V before stenting to grade I–II after stenting. During the follow-up, one patient experienced re-stenosis of the stent. Average survival time was 185.7 days (range, 96–285 days) after the stenting procedure.CONCLUSIONSubcarinal ventilation-assisted Y-shaped stent insertion under local anesthesia can be an effective, simple, and safe method for lower tracheal-carinal-main bronchial complex stenosis

Evolutionary and regulatory pattern analysis of soybean Ca2+ ATPases for abiotic stress tolerance

P2-type Ca2+ ATPases are responsible for cellular Ca2+ transport, which plays an important role in plant development and tolerance to biotic and abiotic stresses. However, the role of P2-type Ca2+ ATPases in stress response and stomatal regulation is still elusive in soybean. In this study, a total of 12 P2-type Ca2+ ATPases genes (GmACAs and GmECAs) were identified from the genome of Glycine max. We analyzed the evolutionary relationship, conserved motif, functional domain, gene structure and location, and promoter elements of the family. Chlorophyll fluorescence imaging analysis showed that vegetable soybean leaves are damaged to different extents under salt, drought, cold, and shade stresses. Real-time quantitative PCR (RT-qPCR) analysis demonstrated that most of the GmACAs and GmECAs are up-regulated after drought, cold, and NaCl treatment, but are down-regulated after shading stress. Microscopic observation showed that different stresses caused significant stomatal closure. Spatial location and temporal expression analysis suggested that GmACA8, GmACA9, GmACA10, GmACA12, GmACA13, and GmACA11 might promote stomatal closure under drought, cold, and salt stress. GmECA1 might regulate stomatal closure in shading stress. GmACA1 and GmECA3 might have a negative function on cold stress. The results laid an important foundation for further study on the function of P2-type Ca2+ ATPase genes GmACAs and GmECAs for breeding abiotic stress-tolerant vegetable soybean