Terms Of Health Care Services Research Articles

Health-Seeking Behaviour and the use of Artificial Intelligence-based Healthcare Chatbots among Indian Patients

Artificial Intelligence (AI) based healthcare chatbots can scale up healthcare services in terms of diagnosis and treatment. However, the use of such chatbots may differ among the Indian population. This study investigates the influence of health-seeking behaviour and the availability of traditional, complementary and alternative medicine systems on healthcare chatbots. A quantitative study using a survey technique collects data from the Indian population. Items measuring the awareness of chatbot’s attributes and services, trust in the chatbots, health-seeking behaviour, traditional, complementary and alternative medicine, and use of chatbots are adapted from previous scales. A convenience sample is used to collect the data from the urban population. 397 samples were fetched, and statistical analysis was done. Awareness of the chatbot’s attributes and services impacted the trust in the chatbots. Health-seeking behaviour positively impacted the use of chatbots and enhanced the impact of trust of a chatbot on the use of a chatbot. Traditional, complementary and alternative medicine was not included in the chatbot, which negatively impacted the use of chatbots. At the same time, it dampened the impact of trust in chatbots on the use of chatbots. The study was limited to the urban population and a convenience sampling because of the need to use the Internet and a smart device for accessing the chatbots. The results of the study need to be used cautiously. The results can be inferred from the relationships’ existence rather than the impact’s magnitude. The study’s outcome encourages the availability of chatbots due to the health-seeking behaviour of the Indian urban population. The study also highlights the need for creating intelligent agents with knowledge of Traditional, complementary and alternative medicine. The study contributes to the knowledge of using chatbots in the Indian context. When earlier studies focus mainly on the chatbot features or user characteristics in the intention studies, this study looks at the healthcare system and the services unique to India.

A qualitative study on how intimate partner violence against women changes, escalates, and persists from pre- to postseparation.

Research has focused on intimate partner violence (IPV) against women either before or after separation, but little attention has been paid to the changes in and persistence of violent behaviors from one situation to the next. This study contributes to the literature by comparing the changes in types and frequencies of abusive behaviors of women's former husbands. This allows us to understand how mechanisms of power are enacted through IPV both before and after separation. We interviewed 19 women in the Midwestern United States who had experienced IPV by their former husbands and had subsequently divorced them. Data were analyzed using qualitative content analysis. The findings suggest that verbal abuse and using children were the most common forms of IPV both pre- and postseparation. Many preseparation behaviors were replaced by other forms of abuse; for example, physical abuse was not experienced after separation. Some forms of IPV, such as stalking and economic abuse, escalated after separation. This reveals that exerting control over women through nonphysical forms of IPV was more common after separation. In particular, using axial and selective coding approach, our findings present three composite narratives of women's experiences of the changes in, and the escalation and persistence of, the violence they faced. The three composite narratives show how abusive behaviors are situated within patriarchal notions of dominance, power, and control over women and their children. The implications of the findings are discussed in terms of healthcare services, advocacy-based victim assistance, school officials, and the courts.

Exploring the Mobility of Older Adults in Urban Environments: A Proposal

The issue of ageing is a global concern, and as urban areas develop, the proportion of citizens aged 60 and over increases. The percentage of Malaysians aged 65 and older increased from 6.5% in 2018 to 6.7% in 2019. In a decade, Malaysia is anticipated to attain the status of an ageing nation, with at least 15 percent of the population being 60 or older. By 2056, Malaysia will be a "super-aged society," as 20% of its population will be over the age of 65. In accordance with the 11th Malaysian Plan (2016–2020), Malaysia has launched the Smart City Initiative to prioritise the welfare of its 'rakyat' people. In addition, the government has unveiled the Intelligent Transport System Blueprint (2017–2022) to modernise the existing transport system. The global trend of an ageing population influences numerous aspects and facilities, including healthcare, financial services, urban planning, transportation, and religious centres. To improve the quality of life for the elderly, their residential environment must be modified. In terms of healthcare services and physical accessibility, elderly mobility presents difficulties. Consequently, the primary objective of this study is to investigate the factors that enable elderly people with smart mobility to access public spaces and transport facilities. To achieve these goals, the research design employs a qualitative approach. This study contributes to the development of smart cities and transport planning, which can support the sustainable mobility of the elderly in Malaysia, a nation confronting the challenges of an ageing population. In addition, the study will address the requirements of the elderly by incorporating the ageing population into national development plans and reevaluating existing planning alongside physical development zones. These initiatives are consistent with the National Sustainable Development Goals (SDGs), which seek to improve the quality of life for the elderly population.

Measuring the extent of patient satisfacation with the services provided by health care in Madinah

The aim of this study was to identify the level of quality of healthcare services provided at the Madinah hospital and to measure the impact of the quality of healthcare services on patient satisfaction. The study also aimed to provide suggestions and recommendations to the hospital on how to improve the quality of healthcare services to positively impact patient satisfaction. The research will use a descriptive methodology, which involves identifying variables and phenomena related to the study, as well as an analytical methodology that analyzes the data obtained through research tools using statistical methods to achieve the study's purpose. The study found that there is a high level of quality of healthcare services in terms of their dimensions (tangibles, reliability, safety, empathy, responsiveness), as well as a high level of patient satisfaction with healthcare services in Madinah. Furthermore, there is a statistically significant positive correlation between the level of quality of healthcare services and patient satisfaction. Specifically, for every 1% increase in the quality of healthcare services, patient satisfaction increased by 0.546%.

Is a right to health a means to protect public health? South Africa as a model for a communitarian interpretation of the right to health for the promotion of public health

ABSTRACT The right to health has primarily been developed and understood as an individualistic right and framed in terms of healthcare services. Public health and disease prevention have become increasingly important, particularly with the increasing occurrence of novel pandemics. The ability of the traditional framing of the right to health is less helpful in contexts where one seeks to apply a human rights-based approach to public health interventions. Though it has been posited that this may be remedied through the introduction of a collective right to public health, the South African experience illustrates the potential of the existing right to health to support public health efforts. Drawing on the African concept of ‘ubuntu’, one can adopt a communitarian approach to the right to health to enforce and protect the right, even where identifying discrete rights-holders and beneficiaries is challenging. This paper further argues that this communitarian approach to the right to health can ameliorate some difficulties experienced with judicialisation of health in other jurisdictions. The South African experience of judicial enforcement of the right to healthcare is used to illustrate the potential value of utilising a communitarian approach to the development of the right to health to include public health.

Swimming Together Upstream: How to Align MLP Services with U.S. Healthcare Delivery.

Medical-legal partnership (MLP) embeds attorneys and paralegals into care delivery to help clinicians address root causes of health inequities. Notwithstanding decades of favorable outcomes, MLP is not as well-known as might be expected. In this essay, the authors explore ways in which strategic alignment of legal services with healthcare services in terms of professionalism, information collection and sharing, and financing might help the MLP movement become a more widespread, sustainable model for holistic care delivery.

A Hybrid Hesitant Fuzzy Model for Healthcare Systems Ranking of European Countries

Ranking several countries on a specific area may require the consideration of various factors simultaneously. To obtain a ranking of countries, the development of analytical approaches, which can aggregate opinions of a group of people on various criteria, is essential. The main aim of this study was to propose such a ranking approach for European countries in terms of healthcare services. To this end, a hybrid group decision-making model based on Hesitant Fuzzy Linguistic Terms Set (HFLTS) and Hesitant Fuzzy Technique of Order Preference by Similarity to Ideal Solution (HF-TOPSIS) is presented in this study. Importance degree of indicators were determined by the HFLTS-based group decision-making approach, and then HF-TOPSIS was used to obtain the rank of countries. According to the results obtained by the proposed model, Austria, Sweden and Finland are the best European countries in terms of healthcare services. Moreover, two comparative analyses, one for the utilization of different hesitant fuzzy distance measures in HF-TOPSIS and one for the ranking of countries obtained by utilizing TOPSIS, return some variations in country rankings. While Austria remained the best country for all distance measures in the hesitant fuzzy environment, Luxemburg was found to be the best for the deterministic case of TOPSIS.

The Impact of The COVID-19 Pandemic on the Management of Chronic Disease in South Africa: A Systematic Review

Introduction: The abrupt development of the coronavirus (COVID-19) pandemic has posed a threat to persons with chronic diseases' compliance with treatment, which is critical to improving their health, life expectancy, and lowering death and morbidity rates. The public health control measures for the pandemic have been heavily politicized. The focus on the COVID-19 epidemic has resulted in a neglect for chronic disease management. As a result, the goal of this study was to review the literature in order to gain a broader perspective on how the COVID-19 pandemic has impacted chronic disease management, as well as to investigate various strategies to deal with similar occurrences in the future when faced with medical emergencies, in order to reduce the potential harm of these measures to non-communicable disease control. Methodology: To analyze and identify full-text studies relevant to the influence of COVID-19 on the management of chronic diseases conducted in an African environment from 2019 to 2021, the suggested reporting items for systematic reviews and meta-analyses were used. Six databases were searched to find relevant studies, which include CINAHL Plus (EBSCO), PubMed, Google Scholar, Medline, ProQuest, and APA PsychINFO. Researchers performed a quality assessment for each included paper prior to data synthesis, as well as a formal risk-of-bias assessment. Results: Out of 119 abstracts reviewed, 17 full-text studies were included. Three themes were identified: the impact of COVID-19 on the healthcare system; the psychological impact on people with chronic diseases and healthcare providers; and the digitalization of healthcare services. The majority of studies were conducted in South Africa and other African countries in collaboration with western countries. The majority of studies focused on lessons learned during periods of strict public health measures, however a few empirical investigations of patients or healthcare providers were done. It is recommended that African countries should develop an integrated community-based non-communicable disease (NCD) and infectious disease care model and protocols, initiate innovative ways of central dispensing, pre-packaging and home delivery of medications to stable patients, use of telemedicine, and emphasize mental health services during medical emergencies. Contribution: The study’s findings could improve policy implementation regarding the management of chronic diseases during a medical emergency; in this case, COVID-19. It could also improve self-care management. The main goal is to maintain adherence and compliance with treatment to reduce complications and the disease burden. The study mainly focused on the African context. Conclusion: The literature revealed that the COVID-19 pandemic has had a severe impact on the management of chronic diseases and disrupted access to related healthcare services in terms of prevention, diagnosis, routine clinical care, and self-care. In addition, the mental health of both patients and healthcare providers has been affected. Chronic diseases should also be considered a public health emergency and should be given the same attention and priority as infectious diseases during a pandemic to reduce the burden of disease, especially in low and middle-income African countries already experiencing a shortage of resources. Rather than depending on the researcher's opinion, viewpoint, and notes taken during the COVID-19 lockdown, primary investigations should be done to address the inadequacies brought to light on the management of chronic diseases due to COVID-19.

A Novel Histological Dataset and Machine Learning Applications

Histology has significant importance in the medical field and healthcare services in terms of microbiological studies. Automatic analysis of tissues and organs based on histological images is an open problem due to the shortcomings of necessary tools. Moreover, the accurate identification and analysis of tissues that is a combination of cells are essential to understanding the mechanisms of diseases and to making a diagnosis. The effective performance of machine learning (ML) and deep learning (DL) methods has provided the solution to several state-of-the-art medical problems. In this study, a novel histological dataset was created using the preparations prepared both for students in laboratory courses and obtained by ourselves in the Department of Histology and Embryology. The created dataset consists of blood, connective, epithelial, muscle, and nervous tissue. Blood, connective, epithelial, muscle, and nervous tissue preparations were obtained from human tissues or tissues from various human-like mammals at different times. Various ML techniques have been tested to provide a comprehensive analysis of performance in classification. In experimental studies, AdaBoost (AB), Artificial Neural Networks (ANN), Decision Tree (DT), Logistic Regression (LR), Naive Bayes (NB), Random Forest (RF), and Support Vector Machines (SVM) have been analyzed. The proposed artificial intelligence (AI) framework is useful as educational material for undergraduate and graduate students in medical faculties and health sciences, especially during pandemic and distance education periods. In addition, it can also be utilized as a computer-aided medical decision support system for medical experts to minimize spent-time and job performance losses.

The patient journey of newly arrived asylum seekers and responsiveness of care: A qualitative study in Germany.

BackgroundResearch on health and healthcare for asylum seekers and refugees (ASR) has focused strongly on accessibility and legal entitlements, with quality of care receiving little attention. This study aimed to assess responsiveness, as non-medical quality of care, in the narratives of ASR patients recently arrived in Germany.Methods31 ASR with existing medical conditions were recruited in six refugee reception centres and three psychosocial centres. Semi-structured, qualitative interviews were conducted which reconstructed their patient journey after arrival in Germany. Interviews were recorded, transcribed verbatim and evaluated using thematic analysis.ResultsThe experiences of participants throughout the patient journey provided a rich and varied description of the responsiveness of health services. Some dimensions of responsiveness, including respectful treatment, clear communication and trust, resurfaced throughout the narratives. These factors were prominent reasons for positive evaluations of the health system, and negative experiences were reported in their absence. Other dimensions, including cleanliness of facilities, autonomy of decision-making and choice of provider were raised seldomly. Positive experiences in Germany were often set in contrast to negative experiences in the participants’ countries of origin or during transit. Furthermore, many participants evaluated their experience with healthcare services in terms of the perceived technical quality of medical care rather than with reference to responsiveness.ConclusionThis qualitative study among ASR analysed patient experiences to better understand responsiveness of care for this population. While our results show high overall satisfaction with health services in Germany, using the lens of responsiveness allowed us to identify particular policy areas where care can be strengthened further. These include in particular the expansion of high-quality interpreting services, provision of professional training to increase the competency of healthcare staff in caring for a diverse patient population, as well as an alignment between healthcare and asylum processes to promote continuity of care.

Evaluating Nursing Staff Perception of Hospital Readiness for Continuity of Essential Health Care Services and Surge Capacity in Line With COVID-19.

To evaluate nursing staff' perception of hospital readiness for continuity of essential health care services and surge capacity in line with COVID-19. A total of 300 nurses were recruited from one hospital in Saudi Arabia. They completed self-administered, online questionnaires. The questionnaire assessed participants' socio-demographic data and their perceptions regarding hospital readiness for continuity of essential health care services and surge capacity in line with COVID-19. The findings revealed that nursing staff had a moderate mean score regarding hospital readiness for continuity of health care services (3.89 ± 0.61) and an average mean value regarding surge capacity of 3.83 ± 0.63. Also, the value of R2 of surge capacity in healthcare can predict 82.9% of the variance in hospital readiness for continuity of health care services in terms of surge capacity. Hospital administrators could propose hospital regulations and protocols for the management of confirmed and suspected COVID-19 patients in addition to designing a continuing education program for health professionals at all levels related to prevention, control, and management of COVID-19 suspected and confirmed patients.

Quality disparity in terms of clients’ satisfaction with selected exempted health care services provided in Ethiopia: Meta-analysis

IntroductionIn Ethiopia; even though utilization of health care services has been improved after the introduction of user fee exemption, little is known about the quality of the services. There are fragmented studies on the output dimension of quality of health care services particularly on clients’ satisfaction. Therefore this study aims to assess overall quality (in terms of clients’ satisfaction) and its disparity among users of selected exempted health care services provided in Ethiopia. MethodsThe Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) guideline was used to undertake this study. Both published and unpublished articles conducted in Ethiopia on the quality of health care services in terms of clients’ satisfaction dimensions were searched. A total of 750 articles were retrieved through international databases (Scopus, MEDLINE/PubMed, Science Direct, Google Scholar and Cochrane Library) and national digital library repositories (Addis Ababa University’s digital library repository); 703 of which were excluded while only 47 articles were included in the meta-analysis. The search for articles was conducted during the period 03 December 2019 to 28 January 2020. For methodological qualities of the included articles assessment, a modified version of the Newcastle-Ottawa Scale adapted for cross-sectional studies was used. R version 3.6.1 and stata version 14 soft wares were used for analysis. A random-effects model was used to calculate pooled estimates. The I2 tests were used to assess the heterogeneity of the studies. ResultsThe pooled overall prevalence of included 47 studies revealed that clients’ satisfaction among users of selected exempted health care services in Ethiopia was 70% (95% CI: 64, 74%). In subgroup analysis; the lowest prevalence of clients’ satisfaction was observed among users of obstetrics maternal health care services with the prevalence of 65.04% (95% CI: 57.50, 72.58). ConclusionThis study found that more than one-third of respondents; was not satisfied with exempted health care services. There is slight difference in satisfaction of clients across type of exempted health care services and regions. Policy and decision makers in Ethiopia shall design strategies to optimize quality of health care services besides exemption of its costs.it is also strongly recommend that a special emphasis shall be given to obstetric health care services provision. Moreover, concerned stakeholders’ (ministry of health, etc.) should strengthen compassionate respectful care provision in public health facilities; beside to removing user fees.

Factors necessary for effective corporate waqf management for Malaysian public healthcare

PurposeThis research paper aims to determine the factors needed to propose a platform where waqf (Islamic endowment) organizations can collaborate with government public hospitals to develop corporate waqf hospitals. Consequently, the elements of governance and sustainability are included in the management of corporate waqf hospitals thereby leading to the corporatization of public hospitals.Design/methodology/approachThis study adopts the qualitative research methodology and undertakes content analysis of data collected from journal articles, magazines and official websites. Data analysis involves open coding with NVivo 12.FindingsGeneral findings from the literature review have shown that architectural and engineering fundamentals were essential factors in the success of past waqf hospitals of the era between 8th and 14th centuries. In that era, the decentralized waqf-based hospitals employed the mutawalli (the trustee/manager of the waqf assets) to govern the administration of the hospitals. Present corporate waqf hospitals can exploit the elements identified from past waqf-based hospitals and additionally adopt the private-public partnership model in the form of a muḍārabah (profit-sharing contract) agreement to design a sustainable waqf governance model for Malaysian public healthcare services.Research limitations/implicationsThe proposed platform is designed for a corporate waqf model developed in collaboration between Malaysian waqf institutions and public healthcare services. It abides by both the Malaysian fatwa (Islamic rulings) on waqf and the laws of the Malaysian Government.Practical implicationsThere is potential for developing the Malaysian corporate waqf-governance healthcare model which will enable the hospital to provide better quality healthcare to more patients through upgrading the quality of equipment used in hospitals and/or better facilities at equal or lower costs. Consequently, this will not only improve waqf management and distribution but also result in reduction of government expenditure.Social implicationsThis research promotes the concept of a corporate waqf hospital which will provide innumerable beneficial healthcare services in terms of improved healthcare quality at affordable costs to the general public and at no cost to the poor and the underprivileged.Originality/valueAlthough waqf has played an important role as a vehicle for Islamic financing in the society for centuries, a model of collaboration or partnership of waqf with public healthcare services has yet to be explored and developed. With proper corporate governance and well-managed sustainability in a corporate waqf model, this newly developed partnership between waqf institutions and public healthcare providers can be a first step in many more interesting collaborative arrangements that can be established between waqf institutions and public services in the future.

Mobile money and healthcare use: Evidence from East Africa

This paper uses a difference-in-difference framework to estimate the effects of mobile money transfer technology (MMT) on healthcare use in the face of negative health shocks. We use survey data from 2013 to 16 with quarterly observations on about 1800 households of 10 villages in the Kisumu region of Western Kenya. We find evidence that MMT, likely through greater ease of informal borrowing, helps households increase utilization of formal healthcare services in terms of visits to a clinic, consultation and medication expenditures in comparison with non-users of this technology. MMT appears to be complementary with other risk-sharing mechanisms such as farm sales and in-kind transfers.

Determinants of health insurance ownership in Jordan: a cross-sectional study of population and family health survey 2017–2018

ObjectivesWith about one-third of the population living below the poverty line, Jordan faces major healthcare, social and national development issues. Low insurance coverage among the poor and high out-of-pocket expenditure...

MARCOS technique under intuitionistic fuzzy environment for determining the COVID-19 pandemic performance of insurance companies in terms of healthcare services

Assessing and ranking private health insurance companies provides insurance agencies, insurance customers, and authorities with a reliable instrument for the insurance decision-making process. Moreover, because the world’s insurance sector suffers from a gap of evaluation of private health insurance companies during the COVID-19 outbreak, the need for a reliable, useful, and comprehensive decision tool is obvious. Accordingly, this article aims to identify insurance companies’ priority ranking in terms of healthcare services in Turkey during the COVID-19 outbreak through a multi-criteria performance evaluation methodology. Herein, alternatives are evaluated and then ranked as per 7 criteria and assessments of 5 experts. Experts’ judgments and assessments are full of uncertainties. We propose a Measurement of Alternatives and Ranking according to the Compromise Solution (MARCOS) technique under an intuitionistic fuzzy environment to rank insurance companies. The outcomes yielded ten insurance companies ranking in terms of healthcare services in the era of COVID-19. The payback period, premium price, and network are determined as the most crucial factors. Finally, a comprehensive sensitivity analysis is performed to verify the proposed methodology’s stability and effectiveness. The introduced approach met the insurance assessment problem during the COVID-19 pandemic very satisfactory manner based on sensitivity analysis findings.

Klinik Uygulama Rehberlerinin Gelişimi: Bilim Haritalama Analizi

The aims of this study are to see the development of clinical practice guides (CPG) in the field of social sciences, to evaluate its development especially in terms of health management, to identify the prominent subjects in the future, and to discover the relationships among the important subjects of CPGs. Bibliometric mapping method has been used in this study. The studies analyzed by bibliometric mapping were downloaded from the Web of Science Core Collection database and analyzed by the SciMAT science mapping program. The analysis was conducted with the data arranged within the time frames of '1990-1999', '2000-2009' and '2010-2019'. 'Words' were used as the primary analysis parameter. The data gathered from published studies were assessed by strategic diagrams, overlap map, thematic evolution map as well as thematic network map. Performance analysis of the emerging themes was done with the information of h-index and the total citation number of the studies included in bibliometric mapping. This study showed that the most publications on CPG were released in 2017, the USA was the high-ranking country in these publications, the important motor themes were determined as 'clinical guidelines' in the first period, 'clinical practice guidelines' and 'quality' in the second period, and 'management' and 'implementation' in the third period. It can be concluded that, in parallel with the increase of the publications on CPGs, the number of new relevant keywords will continue to increase. It is also evaluated that the studies on applying CPGs into practice, determining the experiences and attitudes of healthcare professionals towards CPGs, diminishing the obstacles on the way of implementing CPGs, evaluating CPGs from the managerial point of view and the effects of CPGs on the healthcare services in terms of quality, efficiency and outcomes will continue to increase soon.

Intelligent Management of Distributed Energy Resources for Increased Resilience and Environmental Sustainability of Hospitals

There is a global trend towards zero-energy or even positive-energy buildings, including healthcare facilities. Energy efficiency activities have been investigated and applied successfully for more than 20 years in healthcare facilities in general and hospitals in particular. It is in the last decade that on-site energy production mainly from photovoltaics has been considered mainly as an extra revenue stream for healthcare facilities. Back-up systems are still diesel generator-based in most cases and only recently has there been interest in unifying the energy systems of healthcare facilities in order to integrate the operation of the main systems of the hospital with the on-site renewable energy production and the back-up systems. Hospitals play a very crucial role in our societies. There is a need to achieve the best results in terms of healthcare services but, at the same time, to reduce the cost of these services without affecting the quality level, to enhance resilience and to increase environmental sustainability. As far as energy is concerned, this is feasible and can be accomplished using energy efficiency interventions and on-site power generation and storage using renewable energy technologies. An Intelligent Energy Management System (IEMS) has to be in place in order to harvest the benefits of all the related subsystems allowing them to operate effectively and harmoniously, while at the same time ensuring the operation of the hospital under extreme conditions, e.g., after a natural disaster. The research concerning IEMSs for hospitals is at its first steps and needs to gain momentum.

Perspective: The Practice of Vascular Surgery in The ‘New Normal Times’

Perspective: The Practice of Vascular Surgery in The ‘New Normal Times’

Abstract IA04: Clinical challenges in oncologic imaging: AI support from image analysis to integrated diagnostics

Abstract The automated analysis of large-scale clinical datasets poses new compelling challenges for data-driven and model-based computational methods in medical imaging. As a matter of fact, the amount of heterogeneous biomedical data is considerably increasing due to the advances in medical imaging acquisition modalities and high-throughput technologies for multi-omics. In addition, electronic health records can be properly integrated to support personalized screening and diagnosis. In such a context, artificial intelligence (AI) is revolutionizing cancer image analysis by relying on sophisticated machine learning and computational intelligence techniques. Therefore, cutting-edge AI methods can enable the shift from organization-centric to patient-centric models, leading to effective multi-institutional health care services in terms of both clinical outcomes and costs. Computerized oncologic image analysis is encouraging the transition from largely qualitative image interpretation to quantitative assessment through automated methods aiming at early detection as well as lesion characterization. Nevertheless, several challenges and opportunities exist: • Reproducible and reliable segmentation methods are required to cope with time-consuming and error-prone manual delineation in laborious human decision-making tasks. As a matter of fact, accurate operator-independent segmentation procedures can improve the robustness of radiomics analyses. • Accurate computer-assisted diagnosis, associated with proper data curation, can reduce the risk of overlooking the diagnosis in a clinical environment. • Prognostic/predictive biomarker discovery by capturing the underlying tumor heterogeneity. • Quantification and monitoring of intra-/intertumoral heterogeneity during the course of the disease, by a proper integration of imaging, clinical, and molecular data on a patient-by-patient level • From a health-economics perspective, increasing costs of highly specific oncologic treatments (including immunotherapies) require accurate patient selection strategies, as well as better biomarkers of treatment response. Currently, many state-of-the-art methods based on deep learning have been achieving outstanding performance. The key to their success is the strong learning ability of fully supervised ML models and the availability of large-scale labeled datasets that include precise annotations. Unfortunately, in biomedical research, collecting such accurate annotations is an expensive process due to the need for domain experts’ knowledge. The generation of large mineable imaging datasets might mitigate this challenge by overcoming data paucity and heterogeneity issues. However, along with the availability of samples, data quality and diversity should be considered by collecting and preparing harmonized datasets. Therefore, the generalization abilities in multi-institutional studies can be improved by exploiting transfer learning and domain adaptation techniques. Finally, the explainability and safety of clinical decision support systems should be guaranteed, by avoiding “black-box” AI models exhibiting unpredictable behaviors. In conclusion, precision oncology should be directed towards the development of integrated radiogenomics paradigms that provide robust computational tools for investigating cancer biology as well as its implications for predicting treatment response. This solution allows for large-scale data collection (from multiple institutions) and continuous learning, by dealing with cyber-security and privacy issues. At present, the ultimate challenge is bridging the gap between AI and clinical practice, by firstly performing well-validated clinical research studies. This step is vital for the final translation and deployment of these advanced AI approaches in precision oncology. Citation Format: Evis Sala. Clinical challenges in oncologic imaging: AI support from image analysis to integrated diagnostics [abstract]. In: Proceedings of the AACR Special Conference on Advancing Precision Medicine Drug Development: Incorporation of Real-World Data and Other Novel Strategies; Jan 9-12, 2020; San Diego, CA. Philadelphia (PA): AACR; Clin Cancer Res 2020;26(12_Suppl_1):Abstract nr IA04.