Developing a Series of AI Challenges for the United States Department of the Air Force

Through a series of federal initiatives and orders, the U.S. Government has been making a concerted effort to ensure American leadership in AI. These broad strategy documents have influenced organizations such as the United States Department of the Air Force (DAF). The DAF-MIT AI Accelerator is an initiative between the DAF and MIT to bridge the gap between AI researchers and DAF mission requirements. Several projects supported by the DAF-MIT AI Accelerator are developing public challenge problems that address numerous Federal AI research priorities. These challenges target priorities by making large, AI-ready datasets publicly available, incentivizing open-source solutions, and creating a demand signal for dual use technologies that can stimulate further research. In this article, we describe these public challenges being developed and how their application contributes to scientific advances

Interaction between Coastal and Oceanic Ecosystems of the Western and Central Pacific Ocean through Predator-Prey Relationship Studies

The Western and Central Pacific Ocean sustains the highest tuna production in the world. This province is also characterized by many islands and a complex bathymetry that induces specific current circulation patterns with the potential to create a high degree of interaction between coastal and oceanic ecosystems. Based on a large dataset of oceanic predator stomach contents, our study used generalized linear models to explore the coastal-oceanic system interaction by analyzing predator-prey relationship. We show that reef organisms are a frequent prey of oceanic predators. Predator species such as albacore (Thunnus alalunga) and yellowfin tuna (Thunnus albacares) frequently consume reef prey with higher probability of consumption closer to land and in the western part of the Pacific Ocean. For surface-caught-predators consuming reef prey, this prey type represents about one third of the diet of predators smaller than 50 cm. The proportion decreases with increasing fish size. For predators caught at depth and consuming reef prey, the proportion varies with predator species but generally represents less than 10%. The annual consumption of reef prey by the yellowfin tuna population was estimated at 0.8±0.40CV million tonnes or 2.17×1012±0.40CV individuals. This represents 6.1%±0.17CV in weight of their diet. Our analyses identify some of the patterns of coastal-oceanic ecosystem interactions at a large scale and provides an estimate of annual consumption of reef prey by oceanic predators

Sentinel node involvement with or without completion axillary lymph node dissection: treatment and pathologic results of randomized SERC trial

International audienceBased on results of clinical trials, completion ALND (cALND) is frequently not performed for patients with breast conservation therapy and one or two involved sentinel nodes (SN) by micro- or macro-metastases. However, there were limitations despite a conclusion of non-inferiority for cALND omission. No trial had included patients with SN macro-metastases and total mastectomy or with >2 SN macro-metastases. The aim of the study was too analyze treatment delivered and pathologic results of patients included in SERC trial. SERC trial is a multicenter randomized non-inferiority phase-3 trial comparing no cALND with cALND in cT0-1-2, cN0 patients with SN ITC (isolated tumor cells) or micro-metastases or macro-metastases, mastectomy or breast conservative surgery. We randomized 1855 patients, 929 to receive cALND and 926 SLNB alone. No significant differences in patient’s and tumor characteristics, type of surgery, and adjuvant chemotherapy (AC) were observed between the two arms. Rates of involved SN nodes by ITC, micro-metastases, and macro-metastases were 5.91%, 28.12%, and 65.97%, respectively, without significant difference between two arms for all criteria. In multivariate analysis, two factors were associated with higher positive non-SN rate: no AC versus AC administered after ALND (OR = 3.32, p 2 involved SN versus ≤2 (OR = 3.45, p = 0.0258). Crude rates of positive NSN were 17.62% (74/420) and 26.45% (73/276) for patient’s eligible and non-eligible to ACOSOG-Z0011 trial. No significant differences in patient’s and tumor characteristics and treatment delivered were observed between the two arms. Higher positive-NSN rate was observed for patients with AC performed after ALND (17.65% for SN micro-metastases, 35.22% for SN macro-metastases) in comparison with AC administered before ALND

Assessment of network module identification across complex diseases

International audienc

A Comparison of Rule-based Analysis with Regression Methods in Understanding the Risk Factors for Study Withdrawal in a Pediatric Study

Regression models are extensively used in many epidemiological studies to understand the linkage between specific outcomes of interest and their risk factors. However, regression models in general examine the average effects of the risk factors and ignore subgroups with different risk profiles. As a result, interventions are often geared towards the average member of the population, without consideration of the special health needs of different subgroups within the population. This paper demonstrates the value of using rule-based analysis methods that can identify subgroups with heterogeneous risk profiles in a population without imposing assumptions on the subgroups or method. The rules define the risk pattern of subsets of individuals by not only considering the interactions between the risk factors but also their ranges. We compared the rule-based analysis results with the results from a logistic regression model in The Environmental Determinants of Diabetes in the Young (TEDDY) study. Both methods detected a similar suite of risk factors, but the rule-based analysis was superior at detecting multiple interactions between the risk factors that characterize the subgroups. A further investigation of the particular characteristics of each subgroup may detect the special health needs of the subgroup and lead to tailored interventions