3D printed biomedical devices and their applications: A review on state-of-the-art technologies, existing challenges, and future perspectives.

3D printing, also known as Additive manufacturing (AM), has emerged as a transformative technology with applications across various industries, including the medical sector. This review paper provides an overview of the current status of AM technology, its challenges, and its application in the medical industry. The paper covers the different types of AM technologies, such as fused deposition modeling, stereolithography, selective laser sintering, digital light processing, binder jetting, and electron beam melting, and their suitability for medical applications. The most commonly used biomedical materials in AM, such as plastic, metal, ceramic, composite, and bio-inks, are also viewed. The challenges of AM technology, such as material selection, accuracy, precision, regulatory compliance, cost and quality control, and standardization, are also discussed. The review also highlights the various applications of AM in the medical sector, including the production of patient-specific surgical guides, prosthetics, orthotics, and implants. Finally, the review highlights the Internet of Medical Things (IoMT) and artificial intelligence (AI) for regulatory frameworks and safety standards for 3D-printed biomedical devices. The review concludes that AM technology can transform the healthcare industry by enabling patients to access more personalized and reasonably priced treatment alternatives. Despite the challenges, integrating AI and IoMT with 3D printing technology is expected to play a vital role in the future of biomedical device applications, leading to further advancements and improvements in patient care. More research is needed to address the challenges and optimize its use for medical applications to utilize AM's potential in the medical industry fully.

Characterization and parametric optimization of additive manufacturing process for enhancing mechanical properties.

Additive manufacturing (AM), also known as 3D printing, is a cutting-edge industrial production technique that enables the creation of lighter, stronger components and systems. Fused deposition modeling (FDM) is a popular AM process for creating prototypes and functional components out of common engineering polymers. The mechanical characteristics of printed items are dramatically altered as a result of various process factors. As a result, it is critical to examine the impact of printing settings on the quality of the printed item. In terms of flexural strength, this study presents an experimental examination into the quality analysis of parameters on printed components utilizing FDM. By adjusting process factors such as layer height, raster width, raster angle, and orientation angle, the experiment was carried out utilizing Taguchi's L18 mixed orthogonal array approach. The UNITEK-94100 universal testing equipment was used to evaluate the flexural strength of Acrylonitrile butadiene styrene (ABS) specimens that had been conditioned as per ASTM D790 standard. The impacts of parameters on experimental results were examined and optimized using the hybrid genetic algorithm with response surface methods, response surface approach, and Taguchi method. When the optimal solutions of each technique were studied, the response surface approach and Taguchi methods were determined to be less promising than the genetic algorithm method.

Prevalence of short interpregnancy interval and its associated factors among pregnant women in Debre Berhan town, Ethiopia.

BACKGROUND: Short inter-pregnancy interval is an interval of <24 months between the dates of birth of the preceding child and the conception date of the current pregnancy. Despite its direct effects on the perinatal and maternal outcomes, there is a paucity of evidence on its prevalence and determinant factors, particularly in Ethiopia. Therefore, this study assessed the prevalence and associated factors of short inter-pregnancy interval among pregnant women in Debre Berhan town, Northern Ethiopia. METHODS: A community based cross-sectional study was conducted among a randomly selected 496 pregnant women in Debre Berhan town from February 9 to March 9, 2020. The data were collected by using an interviewer-administered questionnaire and analyzed using STATA (14.2) statistical software. To identify the predictors of short inter-pregnancy interval, multivariable binary logistic regression was fitted and findings are presented using adjusted odds ratio (AOR) with 95% confidence interval (CI). RESULT: The overall prevalence of short inter-pregnancy interval (<24 months) among pregnant women was 205 (40.9%). Being over 30 years of age at first birth (AOR = 3.50; 95% CI: 2.12-6.01), non-use of modern contraceptive (AOR = 2.51; 95% CI: 1.23-3.71), duration of breastfeeding for less than 12 months (AOR = 2.62; 95% CI: 1.32-5.23), parity above four (AOR = 0.31; 95% CI: 0.05-0.81), and unintended pregnancy (AOR = 5.42; 95% CI: 3.34-9.22) were independently associated factors with short inter-pregnancy interval. CONCLUSION: Despite the public health interventions being tried in the country, the prevalence of short inter-pregnancy interval in this study is high. Therefore, it implies that increasing contraceptive use and encouraging optimal breastfeeding might help in the efforts made to avert the problem.