Brain tumor detection using proper orthogonal decomposition integrated with deep learning networks.

BACKGROUND AND OBJECTIVE: The central organ of the human nervous system is the brain, which receives and sends stimuli to the various parts of the body to engage in daily activities. Uncontrolled growth of brain cells can result in tumors which affect the normal functions of healthy brain cells. An automatic reliable technique for detecting tumors is imperative to assist medical practitioners in the timely diagnosis of patients. Although machine learning models are being used, with minimal data availability to train, development of low-order based models integrated with machine learning are a tool for reliable detection. METHODS: In this study, we focus on comparing a low-order model such as proper orthogonal decomposition (POD) coupled with convolutional neural network (CNN) on 2D images from magnetic resonance imaging (MRI) scans to effectively identify brain tumors. The explainability of the coupled POD-CNN prediction output as well as the state-of-the-art pre-trained transfer learning models such as MobileNetV2, Inception-v3, ResNet101, and VGG-19 were explored. RESULTS: The results showed that CNN predicted tumors with an accuracy of 99.21% whereas POD-CNN performed better with about 1/3rd of computational time at an accuracy of 95.88%. Explainable AI with SHAP showed MobileNetV2 has better prediction in identifying the tumor boundaries. CONCLUSIONS: Integration of POD with CNN is carried for the first time to detect brain tumor detection with minimal MRI scan data. This study facilitates low-model approaches in machine learning to improve the accuracy and performance of tumor detection.

Novel sustainable filter for virus filtration and inactivation.

The COVID-19 pandemic has caused a multi-scale impact on the world population that started from a nano-scale respiratory virus and led to the shutdown of macro-scale economies. Direct transmission of SARS-CoV-2 (Severe Acute Respiratory Syndrome Coronavirus 2) and its variants through aerosolized droplets is a major contributor towards increasing cases of this infection. To curb the spread, one of the best engineered solutions is the use of face masks to prevent the passage of infectious saliva micro-droplets from an infected person to a healthy person. The commercially available masks are single use, passive face-piece filters. These become difficult to breathe in during strenuous activities. Also, they need to be disposed regularly due to accumulation of unwanted particulate and pathogens over time. Frequent disposal of these masks is unsustainable for the environment. In this study, we have proposed a novel design for a filter for enhanced virus filtration, better breathability, and virus inactivation over time. The filter is called Hy-Cu named after its (Hy) drophobic properties and another significant layer comprises of copper (Cu). The breathability (pressure drop across filter) of Hy-Cu is tested and compared with widely used surgical masks and KN95 masks, both experimentally and numerically. The results show that the Hy-Cu filter offers at least 10% less air resistance as compared to commercially available masks. The experimental results on virus filtration and inactivation tests using MS2 bacteriophage (a similar protein structure as SARS-CoV-2) show that the novel filter has 90% filtering efficiency and 99% virus inactivation over a period of 2 h. This makes the Hy-Cu filter reusable and a judicious substitute to the single use masks.

Can family or replacement blood donors become regular volunteer donors?

BACKGROUND: In sub-Saharan Africa (SSA) confirmed viral marker prevalence between family donors (FDs) and first-time volunteer nonremunerated donors (VNRDs) is similar. In a blood service collecting 10 units/1000 inhabitants, a questionnaire examined FD donation conditions and willingness of becoming repeat VNRDs. STUDY DESIGN AND METHODS: Four areas were explored: circumstances of visit to hospital, external pressure, experience of donating, and potential repeat donation. After donation and consent, research assistants administered 25 questions and, according to literacy, helped with translation and completion. RESULTS: Of 513 FDs, three-fourths were males (median age, 27 years). Only 1.3% were unemployed and more than 50% were students or teachers. Ties with hospitalized patient were family (76%), friends (13%), colleagues, or sharing place of worship (10%). Donating blood was the reason for visiting in 16.8% and 20.9% had previously donated blood probably as FDs. In one-third of FDs, the family asked for donation of which 10% was pressured by the unjustified reason that not donating was endangering the patient's life. For two-thirds of FDs, donation was given "because individuals were asked." Donation was a positive experience for 77% of donors, 62% being interested in predonation testing. Repeating donation was acceptable for 99% of 79% FDs answering. DISCUSSION: FDs are active in the population, are willing to donate blood if asked, are submitted to little pressure, do not receive incentives, and accept repeat donation. Except for circumstances of donation, FDs are not different from VNRDs and more directly motivated. They constitute a legitimate and important source to improve the blood supply in SSA.