![]() Accurate survival prediction can help doctors make correct diagnoses with fewer mistakes, thereby improving the treatment quality and quality of life among patients. In the medical analysis domain, survival analysis aims to predict the time of death, cardiac arrest, or occurrence of a specific disease 1. Extensive experiments demonstrate that the proposed method significantly improves the time prediction accuracy when compared with direct prediction of the survival times without guidance and outperforms existing methods. Considering the high resolution of WSIs, we extract tumor patches from WSIs using a pre-trained tumor classifier and apply the graph convolutional network to aggregate information across these patches effectively. ![]() Specifically, we propose to combine these two approaches by extracting the risk prediction features and using them as guides for the survival time prediction. Therefore, in this paper, we present a whole slide image (WSI)-based survival time prediction method that takes advantage of both the risk as well as time prediction. However, it is observed that survival time prediction for the patients, particularly with close observation times, possibly has incorrect orders, leading to low prediction accuracy. ![]() The former focuses on ranking deaths among patients based on the Cox model, whereas the latter directly predicts the survival time of each patient. The proposed method constitutes an easy and direct alternative technique for the objective testing of optical elements for ophthalmic and optometric applications, which can be implemented before invasive, demanding, or costly procedures on real subjects.Deep-learning-based survival prediction can assist doctors by providing additional information for diagnosis by estimating the risk or time of death. The Pearson correlation coefficient was 0.878 for all tested optical elements, which agrees with results obtained by similar works. The objective methodology successfully predicts the trends of the visual acuity through-focus curve for all considered cases. Visual acuity measurements were obtained monocularly from a set of six subjects with paralyzed accommodation for a naked eye and then that eye compensated by four multifocal optical elements. A custom-made monocular visual simulator equipped with active optics was used to implement the objective method and to validate it via subjective measurements. The proposed method utilized imaging of sinusoidal gratings provided by the optical elements and the definition of acuity. We propose, implement, and validate a new objective method for predicting the trends of visual acuity through-focus curves provided by specific optical elements. Note: Author names will be searched in the keywords field, also, but that may find papers where the person is mentioned, rather than papers they authored.Use a comma to separate multiple people: J Smith, RL Jones, Macarthur.Use these formats for best results: Smith or J Smith.For best results, use the separate Authors field to search for author names.Use quotation marks " " around specific phrases where you want the entire phrase only. ![]() Question mark (?) - Example: "gr?y" retrieves documents containing "grey" or "gray".Asterisk ( * ) - Example: "elect*" retrieves documents containing "electron," "electronic," and "electricity".Improve efficiency in your search by using wildcards.Example: (photons AND downconversion) - pump.Example: (diode OR solid-state) AND laser.Note the Boolean sign must be in upper-case. Separate search groups with parentheses and Booleans. ![]()
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