Melánia Puskás

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Verified

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• Master of Science
• PhD Student at Obuda University

Cancer prevention and treatment is one of the most significant public health challenges of the 21st century. Cancer is a serious health problem, and it is the second leading cause of death following cardiovascular diseases. This requires a reliable virtual patient model, which is usually created based on animal studies that precede human studies. P...

Chemotherapy remains one of the predominant treatment modalities for cancer patients. However, current drug dosages and schedules typically do not account for intra-and interindividual pharmacokinetic and pharmacodynamic variations. Our approach aims to formulate individual patient characteristics as mathematical models. By determining the paramete...

The intersection of medicine and engineering holds significant promise for advancing cancer treatment. Traditional chemotherapy, which typically employs maximum tolerable doses, often leads to severe side effects and the development of drug resistance. This study presents a novel approach to optimize chemotherapy treatment plans using a genetic alg...

Chemotherapy is still one of the most commonly used ways of treating cancer. While being very effective, this method has serious side effects which can harm the healthy parts of the body. To optimize chemotherapy, we need to find a balance between minimizing the tumor volume, and minimizing the injected doses, to reduce harmful side effects. By lev...

Animal experiments are often used in cancer research as an alternative to clinical trials to determine the effect of various drugs and other biological conditions on tumor behavior. The tumor volume measurement is necessary in these experiments. The operation of imaging devices is expensive, and it is necessary to anesthetize the animals during the...

Even with the great advancements achieved in the field of medicine, cancer still poses a great threat to humanity, taking millions of lives each year. Chemotherapy is one of the most popular choices in cancer treatment due to its relatively low prices and wide availability. However, since chemotherapy is toxic to the healthy, not just cancer cells,...

Personalizing the drug administration during chemotherapy is a promising direction in healthcare. However, due to the lack of an extensive dataset for optimizing treatment, mathematical models are essential to establish a relationship between the response of the tumor to the drug. The parameters of the mathematical model can be considered as the un...

Optimizing chemotherapy treatments often involves customizing drug dosages for individuals or groups with similar traits. This process relies on converting individual patient characteristics into mathematical parameters in a tumor model. Mathematical tumor models are thus used for treatment generation; the models are validated and tuned (i.e., thei...

Usually, clinical cancer treatment therapies that use chemotherapy are generalized for patients and take into consideration only a few parameters from the patients, for example, body mass, age, and chronic diseases. As one would expect, this information is essential in chemotherapy treatment, but not enough. To improve the efficiency of the drugs w...

The application of engineering in medical practice has a long history; however, these systems are generally used for diagnosis. The cyber-medical system approach combines engineering and biology to enhance the treatment of patients. For example, artificial pancreas systems have proved that the achievements of modern technology can be successfully a...

Nowadays, in many countries, the number of newly registered cancer patients keeps growing despite the recent advancements in the medical field. For this reason, every advancement that could potentially get humanity one step closer to fighting this disease is valuable. The future goal of our research is to create a device capable of measuring the tu...

Automated Drug Delivery (ADD) systems refer to advanced medical technologies and methods designed to transfer pharmaceutical compounds to specific sites within the body in an automated, controlled, precise, and efficient manner. These systems aim to reduce side effects, prevent over-dosage, and improve patient adherence to treatment regimens; moreo...

The application of the achievements of mathematics and informatics greatly helped the development of medicine. Designing personalized therapies using different algorithms is crucial, especially during chemotherapy, to minimize the toxic effects on the patient and avoid resistance, thus ensuring a higher quality of life. In this work, we present an...

In the field of medical research, therapy optimization is a crucial area that deserves significant attention. In chemotherapy, tumor modeling plays an essential role in describing the dynamics and behavior of cancer. The parameters of the model can be used to describe the patients and the tumor, and then optimize the chemotherapy for individuals. A...

Optimizing computer-generated therapy may be one of the most promising tools for future medical treatments. In silico experiments are crucial for therapy planning and testing, this requires a reliable virtual patient model. We present a noise model that can be used to model real measurement noise from mice experiments and add this noise to the virt...

Fluorescent live cell imaging is a widely used method in studying in vitro cell cultures, thus the behavior of in vitro tumor spheroids can be examined cheaply and simply over several days. However, during several days lasting experiments with many measurement points, the strong laser light that excites the fluorescent sample can have a destructive...

The combination of medicine with engineering has great potential. The currently used chemotherapy treatments usually use maximal tolerable doses, which can lead to harmful side effects. By using a mathematical approach, we are able to personalize chemotherapy treatments, using unique patient parameters. We propose an algorithm that is capable of ge...

Nowadays clinical therapies in chemotherapy sessions are generalized for patients, therefore we are working to provide a personalized drug plan to help reduce the drug dosage, causing the reduction of side effects and costs. Also, one benefit of this method is to prevent drug resistance. In order to improve the efficiency of the in vivo experiments...

Personalized therapy based on mathematical foundations is a promising method for treating various types of cancer. By identifying the parameters of mathematical equations, we could gain more information about the patients and the tumor. In previous works, a vast number of training data of virtual scenarios has been generated, then used to train a n...

One of the promising directions in future medicine is the optimization of therapies based on mathematical and engi-neering methods, with which the treatment can be personalized. In personalization, the key issue is the identification of the model parameters. We carry out the identification using artificial neural networks, which require training. W...

Cyber-medical systems are revolutionizing medicine. Mathematical therapy optimization is one of the main pioneering results of cyber-medical system approach. Mathematical therapy optimization is based on a mathematical model. A reliable model with personalized model parameters is crucial for generating optimal treatment. We discuss algorithms for e...

Therapy optimization and personalization in cancer treatment requires reliable mathematical models. A key issue in personalization is the identification of the model parameters. We employ artificial neural networks to identify the model parameters based on few measurements using a priori information about the range of the parameters. The trainig da...

Mathematical models of tumor growth and the effect of therapy is fundamental for personalizing and optimizing anticancer therapies. The aim of the research is to provide a good estimation of personalized tumor model parameters based on measurements carried out on the patient. We use in silico experiments to create a large set of training data in a...