ABSTRACT
INTRODUCTION: Medical readiness continues to be a significant concern for the military. DoD policy directs medical authorities to refer service members to the Disability Evaluation System (DES) when the course of further recovery is relatively predictable or within 1 year of diagnosis, whichever is sooner. The Medical Evaluation Readiness Information Toolset (MERIT) is an application that leverages artificial intelligence within a clinical decision support tool to provide clinicians with predictions of a service member's likelihood of referral to the DES for the top 24 medical conditions that result in separation from the service, which represent more than 90% of all referral cases to the DES since 2000. MATERIALS AND METHODS: Data spanned 19 years and contained records for over 3 million army service members. The MERIT team incorporated a novel approach using a Gamma window function to weight recent medical data more than older medical data in the creation of a "Disease Severity Index" (DSI) that summarized the progression of a health deterioration process per medical condition code. Time-dependent medical encounter data were aggregated into an individual-level DSI. The identified features including the DSI were used in logistic regression and random forest models to predict whether a service member is likely to be referred to the DES. Models were constructed for each of the top 24 unfitting medical conditions. RESULTS: MERIT produced a set of high-performing classification models with area under the receiver operating characteristics curves across all conditions exceeding 0.919 using logistic regression for all conditions. CONCLUSIONS: This project demonstrated with a high degree of accuracy that MERIT, using a combination of ICD codes and personnel records, can be used to develop an individual risk profile for each service member.
Subject(s)
Artificial Intelligence , Military Personnel , Humans , PolicyABSTRACT
We experimentally demonstrate long-wavelength-infrared (LWIR) femtosecond filamentation in solids. Systematic investigations of supercontinuum (SC) generation and self-compression of the LWIR pulses assisted by laser filamentation are performed in bulk KrS-5 and ZnSe, pumped by ${\sim}{145}\;{\rm fs}$â¼145fs, 9 µm, 10 µJ pulses from an optical parametric chirped-pulse amplifier operating at 10 kHz of repetition rate. Multi-octave SC spectra are demonstrated in both materials. While forming stable single filament, 1.5 cycle LWIR pulses with 4.5 µJ output pulse energy are produced via soliton-like self-compression in a 5 mm thick KrS-5. The experimental results quantitatively agree well with the numerical simulation based on the unidirectional pulse propagation equation. This work shows the experimental feasibility of high-energy, near-single-cycle LWIR light bullet generation in solids.
ABSTRACT
We perform single-shot frequency domain holography to measure the ultrafast spatio-temporal phase change induced by the optical Kerr effect and plasma in flexible Corning Willow Glass during femtosecond laser-matter interactions. We measure the nonlinear index of refraction ($ {n_2} $n2) to be $(3.6 \pm 0.1) \times {10^{ - 16}}\;{{\rm cm}^2}/{\rm W} $(3.6±0.1)×10-16cm2/W and visualize the plasma formation and recombination on femtosecond time scales in a single shot. To compare with the experiment, we carry out numerical simulations by solving the nonlinear envelope equation.
