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Halberd Corporation has acquired exclusive licenses to two issued patents and four provisional patent applications related to the extracorporeal treatment of blood-borne diseases and Cerebrospinal Fluid related diseases, with particular focus on the treatment and rapid detection of Covid-19 and other virus`. The issued patents` extracorporeal technology is applicable to a significant number of the most debilitating and often fatal illnesses affecting mankind: PTSD, CTE (Chronic Traumatic Encephalopathy) and Cancer, among others. We have developed an aggressive timetable to advance the development of these breakthrough technologies through laboratory, hospital, and clinical trials. In addition, we have initiated the development of potential patient trial application lists. Our management team has extensive experience and contacts in the medical/pharmaceutical fields as well as a demonstrated track record of launching new business ventures in a competitive environment.
Marino and Company is a Allendale, NJ-based company in the Healthcare, Pharmaceuticals, and Biotech sector.
Founded in 1967, HCRS is a non-profit, community mental health agency serving Vermonters in Windham and Windsor counties. HCRS serves over 4,000 individuals every year through its mental health, substance abuse, and developmental disabilities programs. The Agency provides a wide range of social services that support optimal mental health and functioning.
Premier Healthcare Professionals is a Cumming, GA-based company in the Healthcare, Pharmaceuticals, and Biotech sector.
Carta empowers hospitals to personalize the delivery of care to the individual needs of each patient. Our insight here is that personalizing care is not only good from an outcome/clinical perspective (where most people focus in the context of personalization) but is also the best way to optimize operations. Currently, hospitals have to over provision their resources because they are set up to serve the generic patient; planning ahead for exactly the resources needed– no more, no less– is the best way to gain efficiency. The approach we`re advocating and enabling is to: 1) Find past patients similar to the current one being treated 2) Quantify what exactly happened to them during their journey through the hospital (this is where our model comes in) 3) Use machine learning to project what the particular patient in question will need, and what the patient can expect their experience to be in the hospital We`re applying this approach now to two use cases– supplies projection and bed usage projection– and we have a bunch of other use cases we`re planning on addressing in the future.