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Patients with high-grade serous ovarian cancer suffer poor prognosis and variable response to treatment. Known prognostic factors for this disease include homologous recombination deficiency status, age, pathological stage and residual disease status after debulking surgery. Recent work has highlighted important prognostic information captured in computed tomography and histopathological specimens, which can be exploited through machine learning. However, little is known about the capacity of combining features from these disparate sources to improve prediction of treatment response. Here, we assembled a multimodal dataset of 444 patients with primarily late-stage high-grade serous ovarian cancer and discovered quantitative features, such as tumor nuclear size on staining with hematoxylin and eosin and omental texture on contrast-enhanced computed tomography, associated with prognosis. We found that these features contributed complementary prognostic information relative to one another and clinicogenomic features. By fusing histopathological, radiologic and clinicogenomic machine-learning models, we demonstrate a promising path toward improved risk stratification of patients with cancer through multimodal data integration.

Leprosy is a chronic infectious disease produced by Mycobacterium leprae. In 1997 Venezuela reached the goal of elimination of leprosy as a public health problem (according to the World Health Organization a prevalence rate of ≤ 1/10,000 inhabitants), but five states still had prevalence rates over that goal. For this study we selected Cojedes State, where prevalence rates remain over the elimination goal.Evaluate the real leprosy situation in high-prevalence areas of Cojedes State.Seven communities of Cojedes State were selected because they had the highest historic prevalence, as well as the highest prevalence in the year to be studied (1997).A rank correlation using Spearman's test comparing historical prevalence rates (1946-1996) and detection rates (1998-2004) gave a statistically significant P0.05 value. Diagnosed leprosy cases were as follows: age: 3.2% under 15 years old; sex: male/female rates between 60% and 91.66% males. The highest number of cases were paucibacillary forms: indeterminate leprosy (33.07%) and borderline tuberculoid leprosy (32.28%); tuberculoid leprosy (7.00%); and multibacillary cases (lepromatous leprosy, LL) were only 2.36%. Bacteriologically, 18.52 patients were M. leprae positive. At the moment of diagnosis, 96.6% showed no disabilities, 3.4% showed grade I disabilities, and there were no grade II or III disabilities.This study confirms that several communities in Cojedes State have extremely high leprosy rates.