Enhance Patient Care Research Articles

Functional assessment in patients undergoing total hip arthroplasty.

Conventional patient-reported surveys, used for patients undergoing total hip arthroplasty (THA), are limited by subjectivity and recall bias. Objective functional evaluation, such as gait analysis, to delineate a patient's functional capacity and customize surgical interventions, may address these shortcomings. This systematic review endeavours to investigate the application of objective functional assessments in appraising individuals undergoing THA. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were applied. Eligible studies of THA patients that conducted at least one type of objective functional assessment both pre- and postoperatively were identified through Embase, Medline/PubMed, and Cochrane Central database-searching from inception to 15 September 2023. The assessments included were subgrouped for analysis: gait analysis, motion analysis, wearables, and strength tests. A total of 130 studies using 15 distinct objective functional assessment methods (FAMs) were identified. The most frequently used method was instrumented gait/motion analysis, followed by the Timed-Up-and-Go test (TUG), 6 minute walk test, timed stair climbing test, and various strength tests. These assessments were characterized by their diagnostic precision and applicability to daily activities. Wearables were frequently used, offering cost-effectiveness and remote monitoring benefits. However, their accuracy and potential discomfort for patients must be considered. The integration of objective functional assessments in THA presents promise as a progress-tracking modality for improving patient outcomes. Gait analysis and the TUG, along with advancing wearable sensor technology, have the potential to enhance patient care, surgical planning, and rehabilitation.

Evaluation of the impact of an integrated simulation model in basic life support training on knowledge and practice: A randomized control trial in Jordanian hospitals

This study aims to evaluate the effectiveness of simulation training (ST) in improving nurses' knowledge and practice, which is essential in the nursing field, particularly among nurses in Jordanian hospitals. ST has the potential to significantly enhance patient care outcomes. A Randomized Control Trial was conducted in five hospitals in Jordan, using three repeated measurement tests: a pre-test, an immediate post-test after the intervention, and a post-test three months later. The nonparametric Mann-Whitney statistical test showed that the control and experimental groups were similar, with no significant differences in the participants' demographic characteristics. The Independent T-test confirmed the similarity of the pre-test results in the control group's knowledge and practice and the intervention group's mean scores. The simulation intervention proved to be highly effective in enhancing Basic Life Support (BLS) knowledge and practice among nurses. It nearly doubled the knowledge pre-test percentage from 40% to 75.35% in the immediate post-test, improving the scores from poor in the pre-test to excellent in the post-test. This significant improvement highlights the importance of simulation training in enhancing nurses' knowledge and practice. Similarly, ST significantly increased the average practice score percentage from 47.5% to 70% after the intervention, demonstrating its substantial impact. In conclusion, BLS simulation is a highly efficient educational method that helps participants acquire knowledge and skills. Simulation training prepares learners to activate cardiopulmonary resuscitation (CPR) quickly and correctly in case of cardiopulmonary arrest. Therefore, simulation in training should be expanded in the nursing curriculum.

The Botulinum Toxin Innovation: From Powder to Liquid.

Botulinum toxin (BoNT) has evolved as a popular treatment for various medical and aesthetic conditions since the 1980s. The emergence of new liquid formulation BoNT products in the industry highlights the need to evaluate the value and advantages of these modern formulations. The aim of this review was to assess and compare the expected difference in practice between liquid and powder formulation BoNT products. This article involves a review of pertinent guidelines, product information from manufacturers, available database for safety reports, and survey results. Guidelines and safety reports have pointed out potential risks in the reconstitution process, while medication preparation steps are simplified in liquid formulation. The shift toward ready-to-use liquid products can mitigate risks related with reconstitution errors and potentially enhancing patient care by saving time and cost associated with medication preparation.

Advancements in prognostic markers and predictive models for intracerebral hemorrhage: from serum biomarkers to artificial intelligence models.

Intracerebral hemorrhage (ICH) is a severe form of stroke with high morbidity and mortality, accounting for 10-15% of all strokes globally. Recent advancements in prognostic biomarkers and predictive models have shown promise in enhancing the prediction and management of ICH outcomes. Serum sestrin2, a stress-responsive protein, has been identified as a significant prognostic marker, correlating with severity indicators such as NIHSS scores and hematoma volume. Its levels predict early neurological deterioration and poor prognosis, offering predictive capabilities comparable to traditional measures. Furthermore, a deep learning-based AI model demonstrated superior performance in predicting early hematoma enlargement, with higher sensitivity and specificity than conventional methods. Additionally, long-term outcome prediction models using CT radiomics and machine learning have achieved high accuracy, particularly with the Random Forest algorithm. These advancements underscore the potential of integrating novel biomarkers and advanced computational techniques to improve prognostication and management of ICH, aiming to enhance patient care and survival rates. The incorporation of serum sestrin2, AI, and machine learning in predictive models represents a significant step forward in the clinical management of ICH, offering new avenues for research and clinical application.

Effectiveness of machine learning and artificial intelligence in formulating radiological reports for faster and more reliable diagnostics

This article explores the transformative impact of machine learning (ML) and artificial intelligence (AI) on radiological investigations. By enhancing diagnostic accuracy and efficiency, AI algorithms especially deep learning models can detect abnormalities in medical images with remarkable precision, often surpassing human radiologists. The integration of AI expedites image analysis and report generation, alleviating radiologist workloads and reducing burnout. AI systems also offer consistent reporting and continuous learning, improving their performance over time through exposure to vast datasets. Despite the significant benefits, challenges such as data privacy, security, and the need for rigorous validation and oversight remain. As AI continues to advance, it is poised to play a crucial role in enhancing patient care and outcomes in radiology.

Clinical phenotypes of sepsis: a narrative review.

Sepsis, characterized by an aberrant immune response to infection leading to acute organ dysfunction, impacts millions of individuals each year and carries a substantial risk of mortality, even with prompt care. Despite notable medical advancements, managing sepsis remains a formidable challenge for clinicians and researchers, with treatment options limited to antibiotics, fluid therapy, and organ-supportive measures. Given the heterogeneous nature of sepsis, the identification of distinct clinical phenotypes holds the promise of more precise therapy and enhanced patient care. In this review, we explore various phenotyping schemes applied to sepsis. We searched PubMed with the terms "Clinical phenotypes AND sepsis" for any type of article published in English up to September 2023. Only reports in English were included, editorials or articles lacking full text were excluded. A review of clinical phenotypes of sepsis is provided. While discerning clinical phenotypes may seem daunting, the application of artificial intelligence and machine learning techniques provides a viable approach to quantifying similarities among individuals within a sepsis population. These methods enable the differentiation of individuals into distinct phenotypes based on not only factors such as infectious diseases, infection sites, pathogens, body temperature changes and hemodynamics, but also conventional clinical data and molecular omics. The classification of sepsis holds immense significance in improving clinical cure rates, reducing mortality, and alleviating the economic burden associated with this condition.

Quantitative BCR::ABL1 Assay Using Digital Real-Time PCR System: Clinical Applications and Insights

Background: Accurate quantification of BCR::ABL1 transcripts is paramount for the management of chronic myeloid leukemia (CML) and Philadelphia-positive acute lymphoblastic leukemia (Ph+ ALL). Despite advancements in real-time reverse transcription PCR (RT-qPCR), the need for more sensitive and precise assays remains. This study evaluated the diagnostic utility of digital reverse transcription PCR (dRT-PCR) for BCR::ABL1 quantification in assessing minimal residual disease (MRD). Material and methods. Twelve patients with CML or Ph+ ALL were included. Peripheral blood or bone marrow samples, collected in PaxGene RNA preservation tubes, were extracted with the automated QIASymphony SP instrument. dRT-PCR conducted on the LOAA analyzer, utilized the Dr. PCR BCR-ABL1 Detection Kit CE_IVD (OPTOLANE Technologies, South Korea). By employing a dual-labeled hydrolysis probe and target-specific primers, this protocol enabled the simultaneous amplification and detection of BCR::ABL1 transcripts e13a2 and e14a2 and ABL1. The resulting copy numbers/reactions were used to calculate the International Scale percentage (%IS) and the molecular reduction (MR) value and analyzed for clinical correlations. Results. Digital RT-PCR demonstrated high precision in quantifying BCR::ABL1 transcripts, the lowest %IS value being 0.02%. A consistent quality RNA sample totalizing 110 ng/reaction was crucial for successful reactions. This assay proved faster and easier than conventional RT-PCR and did not require standards or calibrators. Conclusion. This study supports the feasibility of digital RT-PCR for quantitative analysis. Future objectives for our laboratory include expanding our diagnostic repertoire using this platform, for enhancing patient care.

Dentofacial deformities and their management in prosthodontic practice

Dentofacial deformities encompass a wide range of skeletal and dental discrepancies that can significantly impact a patient's oral function, aesthetics, and overall quality of life. These deformities can arise from congenital, developmental, or acquired factors, each contributing to the complexity of diagnosis and treatment. Congenital conditions, such as cleft lip and palate and genetic syndromes, often result in significant craniofacial anomalies. Developmental disturbances, including hormonal imbalances and nutritional deficiencies, can further exacerbate these conditions. Additionally, trauma, infections, and neoplasms play a critical role in the etiology of acquired dentofacial deformities. Effective management of dentofacial deformities in prosthodontics requires a multidisciplinary approach, integrating orthodontics, oral and maxillofacial surgery, and advanced prosthodontic techniques. Diagnostic advancements, including 3D imaging and digital workflows, facilitate precise planning and customization of prosthetic solutions. Orthodontic treatment and orthognathic surgery are pivotal in correcting skeletal discrepancies and establishing a stable foundation for prosthodontic rehabilitation. Post-surgical prosthodontic interventions involve the use of high-strength ceramics, zirconia, and biocompatible implant materials to restore dental function and aesthetics. Technological advancements have revolutionized prosthodontic practice. computer-aided design and computer-aided manufacturing (CAD/CAM) technology allows for the accurate design and fabrication of prosthetic components, enhancing treatment predictability and efficiency. The development of minimally invasive techniques, such as guided implant surgery and laser applications, has reduced procedural invasiveness and improved patient outcomes. The integration of digital tools and advanced materials has significantly enhanced the precision, durability, and aesthetic quality of prosthetic restorations. Overall, the advances in prosthodontic techniques and materials have greatly improved the management of dentofacial deformities, offering patients better functional and aesthetic results. Continued innovation and research are essential to address the complex challenges associated with these deformities, ultimately enhancing patient care and outcomes in prosthodontic practice.

Advanced outcomes of mixed reality usage in orthognathic surgery: a systematic review

IntroductionOrthognathic surgery (OGS) is a highly sophisticated surgical technique that aims to repair a variety of skeletal and dental abnormalities, including misaligned jaws and teeth. It requires precise preoperative preparation and advanced surgical skills, which are typically learned through years of practical experience in operating rooms or laboratory-based surgical training facilities utilizing cadavers or models. The traditional physical hands-on method of surgical training is still used at OGS. However, this method requires a longer time of preparation. Currently, mixed reality (MR)—a combination of virtual reality and augmented reality technology—is an innovation of OGS. The present study aimed to present a comprehensive review of studies that assessed the advantages of utilizing mixed reality technology in OGS.MethodsA modified Population, Intervention, Comparison, Outcome strategy was performed using a combination of electronic (PubMed, Cochrane, Embase) and manual searches between 2013 and 2023 exploring mixed reality (MR) technology in OGS in the last 10 years. The inclusion criteria were limited to the patient and study model focusing on the clinical application of MR and the associated field of OGS.ResultThe initial search indicated 1731 studies, of which 17 studies were included for analysis. The main results indicated that the use of MR technology in OGS led to high accuracy and time reduction as primary outcomes and cost-effectiveness and skill improvement as secondary outcomes. The review firmly concluded that MR technology exhibited a positive impact on students, trainees, and oromaxillofacial surgeons. However, due to the heterogeneity of the included studies, meta-analyses could not be performed. Collectively, these findings provide strong evidence for the advantages of MR technology in orthognathic surgery.ConclusionMR technology significantly improves OGS planning efficiency by providing pre-surgical information and serving as an intraoperative navigation tool, reducing surgical time without compromising outcomes. Virtual training using MR technology exerts a positive impact on knowledge and skill improvement for OGS. This innovative technology will revolutionize the healthcare system and enhance patient care.

Catalysts for change: A qualitative study of middle managers' perception of nursing professional competence in primary healthcare.

This study aims to explore middle managers' perception of nursing professional competence within the Norwegian primary healthcare service, a sector vital for managing complex patient needs. Semi-structured interviews were conducted with four middle managers across different municipalities in Norway. Qualitative content analyses, following Graneheim and Lundman, were used for analysing the transcription of the interviews and the data collected. The qualitative content analysis revealed three main themes: the significance of advanced competence, challenges related to competence development and the necessity for defining advanced competence. The findings indicate that middle managers recognise the importance of advanced nursing competence in providing comprehensive patient care, notwithstanding challenges in manpower and competence enhancement. This research underlines the significance of investing in increased competence and improved management in primary healthcare and offers valuable insights for healthcare policy and practice to enhance patient care.

Navigating the Metaverse: A New Virtual Tool with Promising Real Benefits for Breast Cancer Patients.

BC, affecting both women and men, is a complex disease where early diagnosis plays a crucial role in successful treatment and enhances patient survival rates. The Metaverse, a virtual world, may offer new, personalized approaches to diagnosing and treating BC. Although Artificial Intelligence (AI) is still in its early stages, its rapid advancement indicates potential applications within the healthcare sector, including consolidating patient information in one accessible location. This could provide physicians with more comprehensive insights into disease details. Leveraging the Metaverse could facilitate clinical data analysis and improve the precision of diagnosis, potentially allowing for more tailored treatments for BC patients. However, while this article highlights the possible transformative impacts of virtual technologies on BC treatment, it is important to approach these developments with cautious optimism, recognizing the need for further research and validation to ensure enhanced patient care with greater accuracy and efficiency.

The Safety Implications of Information Technology in Nursing: Japanese Incident Data Analysis.

This study delves into the impact of Information Technology (IT) on nursing practice in Japan, focusing on patient safety within the 2021-2022 Japanese Medical Accident Report Data. The research aims to understand how IT factors contribute to nursing-related medical incidents in a healthcare landscape rapidly integrating IT. The study identifies IT-related incidents through a retrospective analysis of medical incident reports, primarily in nursing, by analyzing categorized data and free-text descriptions for IT-related keywords. The findings indicate significant IT-related issues, with 'Other EHR Related' problems (36%) and 'EHR Reporting' errors (25%) being the most prevalent. These incidents often involve challenges in patient identification and medication management. The study suggests improvements like enhanced verification processes and automated systems to mitigate these risks. Conclusively, it underscores the dual nature of IT in nursing: while it holds the potential to enhance patient care, it also introduces challenges that necessitate specialized informatics expertise to ensure its beneficial integration into nursing practices.

The role of the hospital pharmacist to guarantee access and continuity of care for the management of epilepsy

In this article the pivotal role of hospital pharmacists in the multidisciplinary management of epilepsy is discussed. Hospital pharmacists are members of national and local ethics committees, oversee clinical trials, and ensure adherence to regulations for patient access to novel therapeutic treatments. They actively contribute to regulatory processes and the definition of prescribing centers. In the post-launch phase, hospital pharmacists are a key member in the multidisciplinary team, they are involved in decisions relating to the local introduction of drugs, in the management of the drug within the hospital structure and with the direct distribution, and to ensure proper and timely treatment. The pharmacovigilance network, including hospital and community pharmacists, monitors and prevents adverse effects related to epilepsy medications and enhances a collaborative approach with specialists to promote prescription appropriateness, targeting therapy for better patient outcomes. Finally, the potential benefits of deprescribing are briefly discussed, underscoring the importance of a multidisciplinary approach involving doctors and clinical pharmacists to gather comprehensive data and enhance patient care in epilepsy management.

The impact of cognitive fusion on stress among nurses: Exploring gender as a moderator controlling for depressive symptoms.

To investigate the influence of cognitive fusion on stress among nurses, with a focus on exploring gender as a moderator among Jordanian nurses controlling for depressive symptoms. Stress is a significant concern among healthcare workers, particularly nurses, given the escalating work demands and organizational constraints. Data were collected from 206 nurses using a cross-sectional design. Participants completed surveys that included measures for cognitive fusion, stress, and depressive symptoms. Statistical analysis included bivariate correlations, independent sample t-tests, and moderation analysis using Hayes PROCESS. The results were reported using The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines. The findings revealed a moderate correlation among stress, cognitive fusion, and depressive symptoms. The regression model explained 42% of the variance in stress, with significant contributions from cognitive fusion, gender, depressive symptoms, and the interaction between cognitive fusion and gender. Gender moderated the relationship between cognitive fusion and stress, indicating differential effects for males and females. This study underscores the importance of cognitive fusion in understanding and managing stress among nurses. The moderating effect of gender highlights the need for tailored interventions. Reducing stress among nurses may benefit their mental health and potentially enhance patient care and treatment outcomes. IMPLICATIONS FORNURSING PRACTICE AND POLICY: The study highlights crucial implications for nursing policy. Addressing cognitive fusion is vital to reducing nurse stress, directly impacting patient care quality and healthcare outcomes. Policymakers should prioritize gender-aware strategies within nursing policies, fostering a less stressful and more supportive work environment. By doing so, healthcare institutions can enhance the well-being of nurses and ultimately improve patient care, aligning with broader healthcare policy objectives of patient safety and quality improvement.

Emerging Applications of Picture Archiving and Communication Systems and Their Impact on Research and Education: A Literature Review.

In recent times, technological advancements have remarkably improved picture archiving and communication system(PACS) capabilities beyond their conventional use in radiology departments. Researchers and instructors have started employing PACS functionalities to improve medical research processes, promote interdisciplinary collaborations, and facilitate learning. To illustrate this point further, the PACS enables researchers to handle and analyze huge amounts of imaging data with superior precision and speed, supporting innovative studies in areas like disease progression, treatment outcomes, and imaging modalities. Moreover, a PACSintegrated with artificial intelligence (AI) algorithms leads to significant improvements in image processing, diagnostic accuracy, and personalized treatment, thus marking a new approach to medical imaging. The PACSsupported by AI is mostly transformative since they allow for improved early disease detection capabilities as well as automated image processing and decision assistance, which increase diagnostic accuracy and clinical outcomes. Such systems can rapidly process large quantities of visual data with an accuracy rate surpassing earlier endeavors. In medical research, however, combining PACSwith AI allows challenging imaging datasets to be examined, thereby making findings that were not previously possible. The capacity to combine imaging outcomes with clinical information is valuable for medical students and professionals in the field of education. They can access extensive medical image collections and case studies using PACS. This link is critical for teaching and learning as it allows students to interact with concrete events and improve their diagnostic accuracy in a controlled environment. This review discusses how the PACS affects educational courses and clinical outcomes based on the available literature. Our aim was not only to outline recent research or developments but also to present a comprehensive overview regarding the growing role played by PACS in the modern healthcare system and academics. Similarly, we look at the challenges and opportunities associated with the wide adoption of PACS, highlighting possible future areas of study or teaching methodologies. Issues such as data security, interoperability, and the need for defined protocols are included to give an exhaustive understanding of what PACS can and cannot do. Through this study, we stress PACS's revolutionary potential in advancing research methodology and educational practices, eventually contributing to enhanced patient care and knowledge dissemination in healthcare areas. The continual growth of PACS technology and its applications is expected to reshape the landscape of medical research and education, making it a vital component in the quest for medical excellence. By knowing the present trends and future potential, stakeholders in healthcare and education may better employ PACS to reach their objectives and boost overall results.

Non-contrast MR angiography: physical principles and clinical applications in chest, abdomen and pelvis imaging.

This review article focuses on the advancements in non-contrast magnetic resonance angiography (NC-MRA) and its increasing importance in body imaging, especially for patients with renal complications, pregnant women, and children. It highlights the relevance of NC-MRA in chest, abdominal, and pelvis imaging and details various bright-blood NC-MRA techniques like cardiac-gated 3D Fast Spin Echo (FSE), balanced Steady-State Free Precession (bSSFP), Arterial Spin Labeling (ASL), and 4D flow methods. The article explains the operational principles of these techniques, their clinical applications, and their advantages over traditional contrast-enhanced methods. Special attention is given to the utility of these techniques in diverse imaging scenarios, including liver, renal, and pelvic imaging. The article underscores the growing importance of NC-MRA in medical diagnostics, offering insights into current practices and potential future developments. This comprehensive review is a valuable resource for radiologists and clinicians, emphasizing NC-MRA's role in enhancing patient care and diagnostic accuracy across various medical conditions.

Depression as a Prognostic Factor in Lower Extremity Amputation for Diabetic Foot: Insights From a Prospective Study on Wound Healing, Infections, and Early Mortality

This study addresses the challenges faced by diabetic patients undergoing lower extremity amputation due to diabetic foot, particularly focusing on the implications for wound healing and early mortality. The wounds at the amputation stump may necessitate multiple surgical interventions. The aim is to identify prognostic factors associated with these outcomes, shedding light on the complexities surrounding the postamputation phase. A prospective study was conducted on 39 diabetic patients who underwent lower extremity amputation due to diabetic foot between 2021 and 2022. Comprehensive preoperative data, encompassing parameters such as blood count, erythrocyte sedimentation rate, C-reactive protein, procalcitonin, hemoglobin A1c, albumin, protein, transferrin, ferritin levels, age, gender, body mass index, smoking habits, dialysis, revascularization, duration of surgery, and the use of tourniquet during the procedure were meticulously recorded. Additionally, cognitive performance and depression status were assessed preoperatively using the Mini-Mental State Examination (MMSE) and Beck Depression Inventory (BDI), respectively. A follow-up period of 3 months postsurgery allowed for the comparison of patients who developed infections at the amputation stump with those who did not, as well as the distinction between patients who survived and those who succumbed to mortality. The study revealed that the use of a tourniquet during surgery significantly increased the risk of infection (p = .027), and higher BDI scores were associated with increased risks of both infection (AUC = 0.814) and mortality (AUC = 0.769), with cut-off scores of 24.0 and 23.5 predicting these outcomes with high sensitivity and specificity, respectively. Additionally, lower MMSE scores were associated with increased short-term postoperative mortality. There were no statistically significant differences between the groups in parameters such as complete blood count, ESR, CRP, procalcitonin, HbA1c, albumin, total protein, transferrin, ferritin levels, age, gender, BMI, smoking, dialysis, revascularization, and surgery duration. This investigation highlights the significance of considering tourniquet usage during amputation, preoperative depression status, and cognitive function in patients who undergo amputation due to diabetic foot. The use of a tourniquet during surgery is a significant risk factor for infection, and elevated BDI scores are strong predictors of both infection and mortality in patients undergoing amputations. The findings underscore the importance of a multidisciplinary neuropsychiatric evaluation preoperatively to enhance patient care and outcomes.

Incidental Findings in Lung Cancer Screening.

While low-dose computed tomography (LDCT) for lung cancer screening (LCS) has been recognized for its effectiveness in reducing lung cancer mortality, it often simultaneously leads to the detection of incidental findings (IFs) unrelated to the primary screening indication. These IFs present diagnostic and management challenges, potentially causing unnecessary anxiety and further invasive diagnostic procedures for patients. This review article provides an overview of IFs encountered in LDCT, emphasizing their clinical significance and recommended management strategies. We categorize IFs based on their anatomical locations (intrathoracic-intrapulmonary, intrathoracic-extrapulmonary, and extrathoracic) and discuss the most common findings. We highlight the importance of utilizing guidelines and standardized reporting systems by the American College of Radiology (ACR) to guide appropriate follow-ups. For each category, we present specific IF examples, their radiologic features, and the suggested management approach. This review aims to provide radiologists and clinicians with a comprehensive understanding of IFs in LCS for accurate assessment and management, ultimately enhancing patient care. Finally, we outline a few key aspects for future research and development in managing IFs.

Impact of Diabetes Mellitus on Outcomes in Patients with Left Ventricular Assist Devices.

Heart failure (HF) represents a significant health burden in the United States, resulting in substantial mortality and healthcare costs. Through the array of treatment options available, including lifestyle modifications, medications, and implantable devices, HF management has evolved. Left ventricular assist devices (LVADs) have emerged as a crucial intervention, particularly in patients with advanced HF. However, the prevalence of comorbidities such as diabetes mellitus (DM) complicates treatment outcomes. By elucidating the impact of DM on LVAD outcomes, this review aims to inform clinical practice and enhance patient care strategies for individuals undergoing LVAD therapy. Patients with DM have higher rates of hypertension, dyslipidemia, peripheral vascular disease, and renal dysfunction, posing challenges to LVAD management. The macro/microvascular changes that occur in DM can lead to cardiomyopathy and HF. Glycemic control post LVAD implantation is a critical factor affecting patient outcomes. The recent literature has shown significant decreases in hemoglobin A1c following LVAD implantation, representing a possible bidirectional relationship between DM and LVADs; however, the clinical significance of this decrease is unclear. Furthermore, while some studies show increased short- and long-term mortality in patients with DM after LVAD implantation, there still is no literature consensus regarding either mortality or major adverse outcomes in DM patients.

Classification of Breast Cancer with Transfer Learning on Convolutional Neural Network Models

Breast cancer is a serious medical condition and a leading cause of death among women. Early and accurate diagnosis is crucial for improving patient outcomes. This study explores the use of Convolutional Neural Networks (CNNs) with Transfer Learning using DenseNet121 and ResNet50 models to enhance breast cancer classification via mammography. Transfer Learning enables CNN models to leverage knowledge learned from larger datasets such as ImageNet to improve performance on specific breast cancer datasets. The dataset comprised medical images with three breast variations: benign, malignant, and normal, totaling 531 data points. Data was split with a 70% training and 30% validation ratio. Two CNN models, AlexNet and ResNet50, were evaluated to compare their performance in classifying these breast cancer types. The experimental results show that AlexNet achieved a training accuracy of 98.01%, while ResNet50 achieved 64.07%. AlexNet demonstrated superior performance in identifying complex patterns in mammography images, resulting in more accurate classification of different breast cancer types. These findings highlight the potential of deep learning applications to support more precise and effective medical diagnostics for breast cancer. This research contributes significantly to the development of AI technologies in healthcare aimed at improving early detection of breast cancer. The implications of this study could expand our understanding of Transfer Learning applications in medical contexts, driving further advancements in this field to enhance patient care and prognosis