Empowering mothers: Advancing maternal health literacy and numeracy through the introduction of Maternal and Child Health Calendar.

Background: The health literacy and numeracy skills of women in Pakistan are very low compared to other low- and middle-income countries.

Objective: The aim of this study was to improve the health literacy and numeracy skills of unschooled women in Northern Pakistan by developing a Maternal and Child Health Calendar (MCHC). The MCHC utilizes locally contextualized icons to promote and enhance service utilization and maternal and child health (MCH) outcomes.

Evaluation of canine detection of COVID-19 infected individuals under controlled settings.

Reverse transcription polymerase chain reaction (RT-PCR) is currently the standard diagnostic method to detect symptomatic and asymptomatic individuals infected with Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). However, RT-PCR results are not immediate and may falsely be negative before an infected individual sheds viral particles in the upper airways where swabs are collected. Infected individuals emit volatile organic compounds in their breath and sweat that are detectable by trained dogs.

Hemodynamic-impact-based prioritization of ventricular tachycardia alarms.

Ventricular tachycardia (V-tach) is a very serious condition that occurs when the ventricles are driven at high rates. The abnormal excitation pathways make ventricular contraction less synchronous resulting in less effective filling and emptying of the left ventricles. However, almost half of the V-tach alarms declared through processing of patterns observed in electrocardiography are not clinically actionable.

Spike sorting by joint probabilistic modeling of neural spike trains and waveforms.

This paper details a novel probabilistic method for automatic neural spike sorting which uses stochastic point process models of neural spike trains and parameterized action potential waveforms. A novel likelihood model for observed firing times as the aggregation of hidden neural spike trains is derived, as well as an iterative procedure for clustering the data and finding the parameters that maximize the likelihood. The method is executed and evaluated on both a fully labeled semiartificial dataset and a partially labeled real dataset of extracellular electric traces from rat hippocampus.