MEDIMAX TECH INC. SPEC MediMax Tech

2108 Series Sagittal Blade (28.9 x 0.64 x 58.7mm)

Tempus ECG-AF is a cardiovascular machine learning-based notification software intended to analyze recordings of 12-lead ECG devices from patients 65 years of age and older. The software employs machine learning techniques to analyze ECG recordings and detect signs associated with a patient experiencing atrial fibrillation and/or atrial flutter (collectively referred to as AF) within the next 12 months. The device is designed to extract otherwise unavailable information from ECGs conducted under the standard of care, to help health care providers better identify patients who may be at risk for undiagnosed AF in order to evaluate them for referral of further diagnostic follow up and address the unmet need of reducing the number of undiagnosed AF patients.

E-Z Clean, Non-stick, PTFE Coated, Electrosurgical Blade Electrode, 2.75 inch (7 cm)

Bayonet ElectroCautery Pencil

ELECTRODE, BLADE, 6.5', SIL-INS

Davol Advantage Single-Use Quick-Disconnect Corbitt Spatula Electrosurgical Attachment with Stick Resistant Tip Coating, 5mm x 33cm

E-Z Clean, Non-stick, PTFE Coated, Electrosurgical Ball Electrode, 5 inch (12.7 cm)

UltraClean Accessory Electrode 1" (2.54 cm) Coated Blade with Extended Insulation

2108 Series Sagittal Blade (28.9 x 0.64 x 58.7mm)

Tempus ECG-AF is a cardiovascular machine learning-based notification software intended to analyze recordings of 12-lead ECG devices from patients 65 years of age and older. The software employs machine learning techniques to analyze ECG recordings and detect signs associated with a patient experiencing atrial fibrillation and/or atrial flutter (collectively referred to as AF) within the next 12 months. The device is designed to extract otherwise unavailable information from ECGs conducted under the standard of care, to help health care providers better identify patients who may be at risk for undiagnosed AF in order to evaluate them for referral of further diagnostic follow up and address the unmet need of reducing the number of undiagnosed AF patients.