Predicting no-show appointments in a pediatric hospital in Chile using machine learning

The Chilean public health system serves 74% of the country’s population, and 19% of medical appointments are missed on average because of no-shows. The national goal is 15%, which coincides with the average no-show rate reported in the private healthcare system. Our case study, Doctor Luis Calvo Mackenna Hospital, is a public high-complexity pediatric hospital and teaching center in Santiago, Chile. Historically, it has had high no-show rates, up to 29% in certain medical specialties. Using machine learning algorithms to predict no-shows of pediatric patients in terms of demographic, social, and historical variables. To propose and evaluate metrics to assess these models, accounting for the cost-effective impact of possible intervention strategies to reduce no-shows. We analyze the relationship between a no-show and demographic, social, and historical variables, between 2015 and 2018, through the following traditional machine learning algorithms: Random Forest, Logistic Regression, Support Vector Machines, AdaBoost and algorithms to alleviate the problem of class imbalance, such as RUS Boost, Balanced Random Forest, Balanced Bagging and Easy Ensemble. These class imbalances arise from the relatively low number of no-shows to the total number of appointments. Instead of the default thresholds used by each method, we computed alternative ones via the minimization of a weighted average of type I and II errors based on cost-effectiveness criteria. 20.4% of the 395,963 appointments considered presented no-shows, with ophthalmology showing the highest rate among specialties at 29.1%. Patients in the most deprived socioeconomic group according to their insurance type and commune of residence and those in their second infancy had the highest no-show rate. The history of non-attendance is strongly related to future no-shows. An 8-week experimental design measured a decrease in no-shows of 10.3 percentage points when using our reminder strategy compared to a control group. Among the variables analyzed, those related to patients’ historical behavior, the reservation delay from the creation of the appointment, and variables that can be associated with the most disadvantaged socioeconomic group, are the most relevant to predict a no-show. Moreover, the introduction of new cost-effective metrics significantly impacts the validity of our prediction models. Using a prototype to call patients with the highest risk of no-shows resulted in a noticeable decrease in the overall no-show rate.</p

From error bounds to the complexity of first-order descent methods for convex functions

This paper shows that error bounds can be used as effective tools for deriving complexity results for first-order descent methods in convex minimization. In a first stage, this objective led us to revisit the interplay between error bounds and the Kurdyka-\L ojasiewicz (KL) inequality. One can show the equivalence between the two concepts for convex functions having a moderately flat profile near the set of minimizers (as those of functions with H\"olderian growth). A counterexample shows that the equivalence is no longer true for extremely flat functions. This fact reveals the relevance of an approach based on KL inequality. In a second stage, we show how KL inequalities can in turn be employed to compute new complexity bounds for a wealth of descent methods for convex problems. Our approach is completely original and makes use of a one-dimensional worst-case proximal sequence in the spirit of the famous majorant method of Kantorovich. Our result applies to a very simple abstract scheme that covers a wide class of descent methods. As a byproduct of our study, we also provide new results for the globalization of KL inequalities in the convex framework. Our main results inaugurate a simple methodology: derive an error bound, compute the desingularizing function whenever possible, identify essential constants in the descent method and finally compute the complexity using the one-dimensional worst case proximal sequence. Our method is illustrated through projection methods for feasibility problems, and through the famous iterative shrinkage thresholding algorithm (ISTA), for which we show that the complexity bound is of the form $O(q^{k})$ where the constituents of the bound only depend on error bound constants obtained for an arbitrary least squares objective with $\ell^1$ regularization

ENSO and interdecadal climate variability over the last century documented by geochemical records of two coral cores from the South West Pacific

The south west Pacific is affected by climatic phenomena such as ENSO (El Ni&#241;o Southern Oscillation) or the PDO (Pacific Decadal Oscillation). Near-monthly resolution calibrations of Sr/Ca, U/Ca and <span style=&quot;font-family: &apos;Symbol, Times New Roman, Times&apos;; font-size: 16px;&quot;>&delta;</span>¹⁸Oc were made on corals taken from New Caledonia and Wallis Island. These geochemical variations could be linked to SST (sea surface temperature) and SSS (sea surface salinity) variations over the last two decades, itselves dependent on ENSO occurrences. On the other hand, near-half-yearly resolution over the last century smoothes seasonal and interannual climate signals, but emphasizes low frequency climate variability

Hurricanes and climate in the Caribbean during the past 3700 years BP

International audienceA multiproxy analysis of lacustrine sediments cored in Grand-Case Pond at Saint-Martin, north of the Lesser Antilles archipelago, reveals three distinct climatic periods for the last 3700 years. From 3700 to ~2500 yr cal. BP and from 1150 yr cal. BP to the present, carbonate mud deposition occurred in connection with pond lowstands. These periods were also punctuated by severe drought events, marked by gypsum laminae, and hurricane landfalls, leading to marine sand inputs into the pond. The intermediate time interval, from 2500 to 1150 yr cal. BP, is typified by black organic mud deposition, suggesting that hypoxic to anoxic conditions prevailed at the pond bottom. These were probably linked with a perennial pond highstand and reflect more uniform and wetter climatic conditions than today. The carbon isotopic composition of the ostracod Perissocytheridea bisulcata shows that the lowest δ13C values are recorded during the hypoxic periods, as a consequence of bacterial recycling of isotopically depleted organic matter. Such a climatic history agrees closely with that documented from other records in the Caribbean area, such as the Cariaco Basin, central coast of Belize or Barbados. By constrast, discrepancies seem to emerge from the comparison between hurricane activity recorded at Saint-Martin on the one hand and Vieques (Puerto Rico) on the other hand. We explain this apparent contradiction by a balance between two distinct storm paths in response to latitudinal shifts of the Intertropical Convergence Zone (ITCZ). Stronger storm activity over the Gulf coast and the inner Caribbean Sea is favoured by a southern position of the ITCZ in connection with dry climatic conditions. Plausible links with the North Atlantic Oscillation (NAO) are also suggested

25. Climate variability of the last five isotopic interglacials: Direct land-sea-ice correlation from the multiproxy analysis of North-Western Iberian margin deep-sea cores

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The glacial ocean productivity hypothesis: The importance of regional temporal and spatial studies

International audienceHigher ocean productivity has often been proposed to explain lower atmospheric carbon dioxide during the last glacial episodes. But recent consideration of marine cores from different areas show that higher local productivity can be postulated for interglacials as well as for glacial periods. Based on the detailed study of two piston cores from the northwest Africa upwelling system, the results presented here, including delta(18)O stratigraphy, organic carbon contents and fluxes, Ti/Al ratios and grain size measurements, clearly indicate that the two cases of sedimentary records can even co-exist within a single upwelling system. This regional heterogeneity is presumably attributed to combined wind stress and sea-level changes that would induce different sedimentary records in the northern and in the southern part of the system. These results emphasize the importance to understand and to model the response of the main kinds of highly productive oceanographic regional systems which are spatially heterogeneous due to complex continent-ocean interactions, or to the presence of mobile hydrodynamic heterogeneities. For such an understanding it is not necessary to acquire a huge amount of core data throughout the world ocean, but to increase the density of cores as well as the regional-scale modelling efforts in systems such as coastal and equatorial upwelling areas, and the migration areas of the southern polar front