Despite many efforts to address the disparities, the underrepresentation of gender, racial, and ethnic minorities in clinical trials remains a problem and undermines the efficacy of treatments on minorities. This paper focuses on the trial site selection task and proposes FRAMM, a deep reinforcement learning framework for fair trial site selection. We focus on addressing two real-world challenges that affect fair trial sites selection: the data modalities are often not complete for many potential trial sites, and the site selection needs to simultaneously optimize for both enrollment and diversity since the problem is necessarily a trade-off between the two with the only possible way to increase diversity post-selection being through limiting enrollment via caps. To address the missing data challenge, FRAMM has a modality encoder with a masked cross-attention mechanism for handling missing data, bypassing data imputation and the need for complete data in training. To handle the need for making efficient trade-offs, FRAMM uses deep reinforcement learning with a specifically designed reward function that simultaneously optimizes for both enrollment and fairness. We evaluate FRAMM using 4,392 real-world clinical trials ranging from 2016 to 2021 and show that FRAMM outperforms the leading baseline in enrollment-only settings while also achieving large gains in diversity. Specifically, it is able to produce a 9% improvement in diversity with similar enrollment levels over the leading baselines. That improved diversity is further manifested in achieving up to a 14% increase in Hispanic enrollment, 27% increase in Black enrollment, and 60% increase in Asian enrollment compared to selecting sites with an enrollment-only model.

In 1962, when astronaut John Glenn was preparing for an orbital mission, mathematician Katherine Johnson was called by the US space agency Nasa for an important task: calculating trajectories. According to Nasa's website, the complexity of the orbital flight, which would make Glenn the first American to orbit Earth, required the construction of a communications network that would link tracking stations around the world to computers in Washington, Florida and Bermuda. These computers were programmed with orbital equations that would control the trajectory of Glenn's Friendship 7 spacecraft. But these machines were also prone to glitches. So, Glenn asked engineers to enlist Johnson to run the same numbers through the same equations programmed into the computer, but by hand, on a desktop mechanical calculating machine.

In the foothills of the Appalachian Mountains in a corner of South Carolina sits a town that should be economically dead. For decades, Greenville was the heart of the state's textile industry--and its economic engine. First attracted by the area's fast-moving rivers as a way to power looms, textile manufacturers employed tens of thousands of people here. Beginning in the 1970s, however, facing competition from lower-cost manufacturing regions like Mexico and Southeast Asia, these companies began to struggle. Over the next decades, many factories closed.

However, all eligible students The American Association for Artificial Technical Papers, Workshop Proposals, are encouraged to apply. Intelligence presents the 2004 Tutorial Forum Proposals, Student After the conference, an expense Spring Symposium Series, to be held Programs, Intelligent Systems report will be required to account for Monday through Wednesday, March Demonstrations, and other related the funds awarded.