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Probabilistic learning to perform pre-onset individualised prediction of disease severity: application to Veno Occlusive Disease
arXiv:2606.06516v1 Announce Type: cross Abstract: We advance a new probabilistic supervised learning approach that permits reliable, automated, and early individualised prediction of the severity with which a disease will develop in a prospective patient. The prediction capacity is illustrated via the pre-transplant prediction of the score of severity of Veno Occlusive Disease (or VOD) in the digital twin (DT) of the considered prospective patient, where this score parametrises the severity...
MH-53E Sea Dragon: Why US navy's mine-hunting is retiring after 40 years
As tensions in the Middle East continue to focus attention on maritime security and the strategic Strait of Hormuz, one aircraft has repeatedly found itself back in the spotlight: the MH-53E Sea Dragon. For nearly four decades, the massive helicopter has served as the US Navy's primary airborne mine countermeasures platform, capable of detecting, sweeping and neutralising naval mines that threaten commercial shipping and military vessels. However, the aircraft is now approaching the end of...
ATN3D: Density-Aware LiDAR-Radar Early 3D Object Detection Under Extreme Sparsity
Announce Type: new Abstract: 3D object detection is the backbone of perception for automated vehicles (AV) and broader intelligent transportation systems applications. Long-range detection is challenging because sensing evidence is sparse; yet this ``long-range'' scenario is routine in traffic. Although >30m is often labeled long-range in computer vision, on roadways it affords only approx.