SchNet - a deep learning architecture for molecules and materials

Deep learning has led to a paradigm shift in artificial intelligence, including web, text and image search, speech recognition, as well as bioinformatics, with growing impact in chemical physics. Machine learning in general and deep learning in particular is ideally suited for representing quantum-mechanical interactions, enabling to model nonlinear potential-energy surfaces or enhancing the exploration of chemical compound space. Here we present the deep learning architecture SchNet that is specifically designed to model atomistic systems by making use of continuous-filter convolutional layers. We demonstrate the capabilities of SchNet by accurately predicting a range of properties across chemical space for \emph{molecules and materials} where our model learns chemically plausible embeddings of atom types across the periodic table. Finally, we employ SchNet to predict potential-energy surfaces and energy-conserving force fields for molecular dynamics simulations of small molecules and perform an exemplary study of the quantum-mechanical properties of C$_{20}$-fullerene that would have been infeasible with regular ab initio molecular dynamics

Societal issues concerning the application of artificial intelligence in medicine

Medicine is becoming an increasingly data-centred discipline and, beyond classical statistical approaches, artificial intelligence (AI) and, in particular, machine learning (ML) are attracting much interest for the analysis of medical data. It has been argued that AI is experiencing a fast process of commodification. This characterization correctly reflects the current process of industrialization of AI and its reach into society. Therefore, societal issues related to the use of AI and ML should not be ignored any longer and certainly not in the medical domain. These societal issues may take many forms, but they all entail the design of models from a human-centred perspective, incorporating human-relevant requirements and constraints. In this brief paper, we discuss a number of specific issues affecting the use of AI and ML in medicine, such as fairness, privacy and anonymity, explainability and interpretability, but also some broader societal issues, such as ethics and legislation. We reckon that all of these are relevant aspects to consider in order to achieve the objective of fostering acceptance of AI- and ML-based technologies, as well as to comply with an evolving legislation concerning the impact of digital technologies on ethically and privacy sensitive matters. Our specific goal here is to reflect on how all these topics affect medical applications of AI and ML. This paper includes some of the contents of the “2nd Meeting of Science and Dialysis: Artificial Intelligence,” organized in the Bellvitge University Hospital, Barcelona, Spain.Peer ReviewedPostprint (author's final draft

A cost-effectiveness analysis of provider and community interventions to improve the treatment of uncomplicated malaria in Nigeria: study protocol for a randomized controlled trial.

BACKGROUND: There is mounting evidence of poor adherence by health service personnel to clinical guidelines for malaria following a symptomatic diagnosis. In response to this, the World Health Organization (WHO) recommends that in all settings clinical suspicion of malaria should be confirmed by parasitological diagnosis using microscopy or Rapid Diagnostic Test (RDT). The Government of Nigeria plans to introduce RDTs in public health facilities over the coming year. In this context, we will evaluate the effectiveness and cost-effectiveness of two interventions designed to support the roll-out of RDTs and improve the rational use of ACTs. It is feared that without supporting interventions, non-adherence will remain a serious impediment to implementing malaria treatment guidelines. METHODS/DESIGN: A three-arm stratified cluster randomized trial is used to compare the effectiveness and cost-effectiveness of: (1) provider malaria training intervention versus expected standard practice in malaria diagnosis and treatment; (2) provider malaria training intervention plus school-based intervention versus expected standard practice; and (3) the combined provider plus school-based intervention versus provider intervention alone. RDTs will be introduced in all arms of the trial. The primary outcome is the proportion of patients attending facilities that report a fever or suspected malaria and receive treatment according to malaria guidelines. This will be measured by surveying patients (or caregivers) as they exit primary health centers, pharmacies, and patent medicine dealers. Cost-effectiveness will be presented in terms of the primary outcome and a range of secondary outcomes, including changes in provider and community knowledge. Costs will be estimated from both a societal and provider perspective using standard economic evaluation methodologies. TRIAL REGISTRATION: Clinicaltrials.gov NCT01350752

A review of rapid serial visual presentation-based brain-computer interfaces

International audienceRapid serial visual presentation (RSVP) combined with the detection of event related brain responses facilitates the selection of relevant information contained in a stream of images presented rapidly to a human. Event related potentials (ERPs) measured non-invasively with electroencephalography (EEG) can be associated with infrequent targets amongst a stream of images. Human-machine symbiosis may be augmented by enabling human interaction with a computer, without overt movement, and/or enable optimization of image/information sorting processes involving humans. Features of the human visual system impact on the success of the RSVP paradigm, but pre-attentive processing supports the identification of target information post presentation of the information by assessing the co-occurrence or time-locked EEG potentials. This paper presents a comprehensive review and evaluation of the limited but significant literature on research in RSVP-based brain-computer interfaces (BCIs). Applications that use RSVP-based BCIs are categorized based on display mode and protocol design, whilst a range of factors influencing ERP evocation and detection are analyzed. Guidelines for using the RSVP-based BCI paradigms are recommended, with a view to further standardizing methods and enhancing the inter-relatability of experimental design to support future research and the use of RSVP-based BCIs in practice

A Cluster Randomised Trial Introducing Rapid Diagnostic Tests into Registered Drug Shops in Uganda: Impact on Appropriate Treatment of Malaria

Background: Inappropriate treatment of malaria is widely reported particularly in areas where there is poor access to health facilities and self-treatment of fevers with anti-malarial drugs bought in shops is the most common form of care-seeking. The main objective of the study was to examine the impact of introducing rapid diagnostic tests for malaria (mRDTs) in registered drug shops in Uganda, with the aim to increase appropriate treatment of malaria with artemisinin-based combination therapy (ACT) in patients seeking treatment for fever in drug shops. Methods: A cluster-randomized trial of introducing mRDTs in registered drug shops was implemented in 20 geographical clusters of drug shops in Mukono district, central Uganda. Ten clusters were randomly allocated to the intervention (diagnostic confirmation of malaria by mRDT followed by ACT) and ten clusters to the control arm (presumptive treatment of fevers with ACT). Treatment decisions by providers were validated by microscopy on a reference blood slide collected at the time of consultation. The primary outcome was the proportion of febrile patients receiving appropriate treatment with ACT defined as: malaria patients with microscopically-confirmed presence of parasites in a peripheral blood smear receiving ACT or rectal artesunate, and patients with no malaria parasites not given ACT. Findings: A total of 15,517 eligible patients (8672 intervention and 6845 control) received treatment for fever between January-December 2011. The proportion of febrile patients who received appropriate ACT treatment was 72·9% versus 33·7% in the control arm; a difference of 36·1% (95% CI: 21·3 – 50·9), p<0·001. The majority of patients with fever in the intervention arm accepted to purchase an mRDT (97·8%), of whom 58·5% tested mRDT-positive. Drug shop vendors adhered to the mRDT results, reducing over-treatment of malaria by 72·6% (95% CI: 46·7– 98·4), p<0·001) compared to drug shop vendors using presumptive diagnosis (control arm). Conclusion: Diagnostic testing with mRDTs compared to presumptive treatment of fevers implemented in registered drug shops substantially improved appropriate treatment of malaria with ACT

The costs of introducing artemisinin-based combination therapy: evidence from district-wide implementation in rural Tanzania

BACKGROUND\ud \ud The development of antimalarial drug resistance has led to increasing calls for the introduction of artemisinin-based combination therapy (ACT). However, little evidence is available on the full costs associated with changing national malaria treatment policy. This paper presents findings on the actual drug and non-drug costs associated with deploying ACT in one district in Tanzania, and uses these data to estimate the nationwide costs of implementation in a setting where identification of malaria cases is primarily dependant on clinical diagnosis.\ud \ud METHODS\ud \ud Detailed data were collected over a three year period on the financial costs of providing ACT in Rufiji District as part of a large scale effectiveness evaluation, including costs of drugs, distribution, training, treatment guidelines and other information, education and communication (IEC) materials and publicity. The district-level costs were scaled up to estimate the costs of nationwide implementation, using four scenarios to extrapolate variable costs.\ud \ud RESULTS\ud \ud The total district costs of implementing ACT over the three year period were slightly over one million USD, with drug purchases accounting for 72.8% of this total. The composite (best) estimate of nationwide costs for the first three years of ACT implementation was 48.3 million USD (1.29 USD per capita), which varied between 21 and 67.1 million USD in the sensitivity analysis (2003 USD). In all estimates drug costs constituted the majority of total costs. However, non-drug costs such as IEC materials, drug distribution, communication, and health worker training were also substantial, accounting for 31.4% of overall ACT implementation costs in the best estimate scenario. Annual implementation costs are equivalent to 9.5% of Tanzania's recurrent health sector budget, and 28.7% of annual expenditure on medical supplies, implying a 6-fold increase in the national budget for malaria treatment.\ud \ud CONCLUSION\ud \ud The costs of implementing ACT are substantial. Although drug purchases constituted a majority of total costs, non-drug costs were also considerable. It is clear that substantial external resources will be required to facilitate and sustain effective ACT delivery across Tanzania and other malaria-endemic countries

Estimating the Number of Paediatric Fevers Associated with Malaria Infection Presenting to Africa's Public Health Sector in 2007

Peter Gething and colleagues compute the number of fevers likely to present to public health facilities in Africa and the estimated number of these fevers likely to be infected with Plasmodium falciparum malaria parasites